Classification_model_for_the_adult_income_data.ipynb

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      "metadata": {
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      "cell_type": "markdown",
      "source": [
        "# Table of Contents"
      ]
    },
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        ">[Table of Contents](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=r3_HX9gdUrcy)\n",
        "\n",
        ">[Income Classification Problem](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=D85_VX0wOur8)\n",
        "\n",
        ">>>[Attribute information:](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=D85_VX0wOur8)\n",
        "\n",
        ">>>[Loading training and the testing data and some data cleaning](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=D85_VX0wOur8)\n",
        "\n",
        ">>>[Some statistics and insights into data](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=VzkPWcDuQzAp)\n",
        "\n",
        ">>>[Some more data pre-processing](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=ura2zX6hSSeh)\n",
        "\n",
        ">>>[Building Classification Algorithms](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=rEianckESmKZ)\n",
        "\n",
        ">>>>[Logistic regression](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=4surG99-SvPv)\n",
        "\n",
        ">>>>>[A function to plot the confusion matrix](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=qAmgYlDVS45p)\n",
        "\n",
        ">>>>[Logistic regression model with LASSO-type penalisation (L1)](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=gB_9Q_gwTFYk)\n",
        "\n",
        ">>>>[Ensemble of Decision Trees Classifier (Extreme Gradient Boosting Classifier)](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=N2lJ4M_ITRSq)\n",
        "\n",
        ">>>>[Cross-validation of the tree based model using 5-fold](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=zKWTqZi8TZUy)\n",
        "\n",
        ">>>[Conclusion based on the 5-fold cross-validation](#updateTitle=true&folderId=1I6abHxBfYUvjHkeR_NTOIAxOrl74iEy2&scrollTo=yZM1tjYWTkp3)\n",
        "\n"
      ]
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      "source": [
        "# Income Classification Problem\n",
        "\n",
        "We use the Adult income data set, which we can get from here: https://archive.ics.uci.edu/ml/machine-learning-databases/adult/\n",
        "\n",
        "We first create some summary charts and tables to explore the data. This is followed by  fitting a classification model to the data. Here we are trying to predict whether an individual earns more or less than $50k. We present the classification error rate and the confusion matrix.  Then we fit several other classification models to the data and check their performance compared to the first model. \n",
        "\n",
        "### Attribute information:\n",
        "\n",
        "age: continuous.\n",
        "\n",
        "workclass: Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked.\n",
        "\n",
        "fnlwgt: continuous.\n",
        "\n",
        "education: Bachelors, Some-college, 11th, HS-grad, Prof-school, Assoc-acdm, Assoc-voc, 9th, 7th-8th, 12th, Masters, 1st-4th, 10th, Doctorate, 5th-6th, Preschool.\n",
        "\n",
        "education-num: continuous.\n",
        "\n",
        "marital-status: Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent, Married-AF-spouse.\n",
        "\n",
        "occupation: Tech-support, Craft-repair, Other-service, Sales, Exec-managerial, Prof-specialty, Handlers-cleaners, Machine-op-inspct, Adm-clerical, Farming-fishing, Transport-moving, Priv-house-serv, Protective-serv, Armed-Forces.\n",
        "\n",
        "relationship: Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried.\n",
        "\n",
        "race: White, Asian-Pac-Islander, Amer-Indian-Eskimo, Other, Black.\n",
        "sex: Female, Male.\n",
        "\n",
        "capital-gain: continuous.\n",
        "\n",
        "capital-loss: continuous.\n",
        "\n",
        "hours-per-week: continuous.\n",
        "\n",
        "native-country: United-States, Cambodia, England, Puerto-Rico, Canada, Germany, Outlying-US(Guam-USVI-etc), India, Japan, Greece, South, China, Cuba, Iran, Honduras, Philippines, Italy, Poland, Jamaica, Vietnam, Mexico, Portugal, Ireland, France, Dominican-Republic, Laos, Ecuador, Taiwan, Haiti, Columbia, Hungary, Guatemala, Nicaragua, Scotland, Thailand, Yugoslavia, El-Salvador, Trinadad&Tobago, Peru, Hong, Holand-Netherlands.\n",
        "\n",
        "### Loading training and the testing data and some data cleaning\n"
      ]
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        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271015121,
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            "displayName": "Divakar Kumar",
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      "source": [
        "import pandas as pd \n",
        "import numpy as np\n",
        "\n",
        "# all columns of the adult data\n",
        "columns = ['age', 'workclass', 'fnlwgt','education','education-num','marital-status','occupation',\n",
        "           'relationship','race','gender','capital-gain','capital-loss','hours-per-week','native-country','income']\n",
        "\n",
        "# read the training file\n",
        "adult_train = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data', names=columns, \n",
        "                      sep=',\\s', na_values=[\"?\"], index_col=False)\n",
        "\n",
        "# read the test file \n",
        "adult_test = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.test', names=columns, \n",
        "                      sep=',\\s', na_values=[\"?\"],skiprows=[0], index_col=False)\n",
        "\n",
        "print(adult_train.shape)\n",
        "print(adult_test.shape)"
      ],
      "execution_count": 1,
      "outputs": [
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          "output_type": "stream",
          "text": [
            "/usr/local/lib/python2.7/dist-packages/ipykernel_launcher.py:10: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n",
            "  # Remove the CWD from sys.path while we load stuff.\n"
          ],
          "name": "stderr"
        },
        {
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          "text": [
            "(32561, 15)\n",
            "(16281, 15)\n"
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          "text": [
            "/usr/local/lib/python2.7/dist-packages/ipykernel_launcher.py:14: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators (separators > 1 char and different from '\\s+' are interpreted as regex); you can avoid this warning by specifying engine='python'.\n",
            "  \n"
          ],
          "name": "stderr"
        }
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          "status": "ok",
          "timestamp": 1530271029327,
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          "elapsed": 458,
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            "displayName": "Divakar Kumar",
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      "cell_type": "code",
      "source": [
        "# Lets check which columns contain the missing values and how many\n",
        "print adult_train.apply(lambda x: sum(x.isna()))\n",
        "print adult_test.apply(lambda x: sum(x.isna()))"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "age                  0\n",
            "workclass         1836\n",
            "fnlwgt               0\n",
            "education            0\n",
            "education-num        0\n",
            "marital-status       0\n",
            "occupation        1843\n",
            "relationship         0\n",
            "race                 0\n",
            "gender               0\n",
            "capital-gain         0\n",
            "capital-loss         0\n",
            "hours-per-week       0\n",
            "native-country     583\n",
            "income               0\n",
            "dtype: int64\n",
            "age                 0\n",
            "workclass         963\n",
            "fnlwgt              0\n",
            "education           0\n",
            "education-num       0\n",
            "marital-status      0\n",
            "occupation        966\n",
            "relationship        0\n",
            "race                0\n",
            "gender              0\n",
            "capital-gain        0\n",
            "capital-loss        0\n",
            "hours-per-week      0\n",
            "native-country    274\n",
            "income              0\n",
            "dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
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            "displayName": "Divakar Kumar",
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      "cell_type": "code",
      "source": [
        "# for somplicity we drop the NaN values this time \n",
        "adult_train = adult_train.dropna(axis = 0)\n",
        "adult_test = adult_test.dropna(axis = 0)\n",
        "\n",
        "print adult_train.shape\n",
        "print adult_test.shape"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(30162, 15)\n",
            "(15060, 15)\n"
          ],
          "name": "stdout"
        }
      ]
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    {
      "metadata": {
        "id": "VzkPWcDuQzAp",
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      "cell_type": "markdown",
      "source": [
        "> I have dropped observations with missing values here only because this is a fairly big data set. However, in a general setting missing values can be easily imputed based on mean, median or model of the column.\n",
        "\n",
        "### Some statistics and insights into data"
      ]
    },
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        "executionInfo": {
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          "timestamp": 1530271103603,
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          "elapsed": 904,
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            "displayName": "Divakar Kumar",
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      "cell_type": "code",
      "source": [
        "# some summary statistics of the numeric columns\n",
        "\n",
        "print \"some descriptive statistics are given as follows: \\n\"\n",
        "print adult_train.describe()\n",
        "print \"\\n\"\n",
        "print \"The correlation structure between the numeric variables are given below: \\n\"\n",
        "print adult_train.corr()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "some descriptive statistics are given as follows: \n",
            "\n",
            "                age        fnlwgt  education-num  capital-gain  capital-loss  \\\n",
            "count  30162.000000  3.016200e+04   30162.000000  30162.000000  30162.000000   \n",
            "mean      38.437902  1.897938e+05      10.121312   1092.007858     88.372489   \n",
            "std       13.134665  1.056530e+05       2.549995   7406.346497    404.298370   \n",
            "min       17.000000  1.376900e+04       1.000000      0.000000      0.000000   \n",
            "25%       28.000000  1.176272e+05       9.000000      0.000000      0.000000   \n",
            "50%       37.000000  1.784250e+05      10.000000      0.000000      0.000000   \n",
            "75%       47.000000  2.376285e+05      13.000000      0.000000      0.000000   \n",
            "max       90.000000  1.484705e+06      16.000000  99999.000000   4356.000000   \n",
            "\n",
            "       hours-per-week  \n",
            "count    30162.000000  \n",
            "mean        40.931238  \n",
            "std         11.979984  \n",
            "min          1.000000  \n",
            "25%         40.000000  \n",
            "50%         40.000000  \n",
            "75%         45.000000  \n",
            "max         99.000000  \n",
            "\n",
            "\n",
            "The correlation structure between the numeric variables are given below: \n",
            "\n",
            "                     age    fnlwgt  education-num  capital-gain  capital-loss  \\\n",
            "age             1.000000 -0.076511       0.043526      0.080154      0.060165   \n",
            "fnlwgt         -0.076511  1.000000      -0.044992      0.000422     -0.009750   \n",
            "education-num   0.043526 -0.044992       1.000000      0.124416      0.079646   \n",
            "capital-gain    0.080154  0.000422       0.124416      1.000000     -0.032229   \n",
            "capital-loss    0.060165 -0.009750       0.079646     -0.032229      1.000000   \n",
            "hours-per-week  0.101599 -0.022886       0.152522      0.080432      0.052417   \n",
            "\n",
            "                hours-per-week  \n",
            "age                   0.101599  \n",
            "fnlwgt               -0.022886  \n",
            "education-num         0.152522  \n",
            "capital-gain          0.080432  \n",
            "capital-loss          0.052417  \n",
            "hours-per-week        1.000000  \n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
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      "cell_type": "markdown",
      "source": [
        ">From the above summary statistics it is clear that the correlation structure among the quantitative variables is fairly week in this case. No two variables shows strong linear relationship among themselves."
      ]
    },
    {
      "metadata": {
        "id": "rkCwfrzmQ_az",
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          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def stacked_plot(data, ind_var, dep_var):\n",
        "  \"\"\"\n",
        "  Function to output the stacked plot of two categorical varaibles. \n",
        "  \n",
        "  Input :\n",
        "  -------------------\n",
        "  data : a pandas data frame \n",
        "  ind_var : first categorical variable in the string format \n",
        "  dep_var : second categorical variable in the sttring format \n",
        "  \n",
        "  Output :\n",
        "  -------------------\n",
        "  Simply plots the stacked bar chart of the categorical variables \n",
        "  \"\"\"\n",
        "  # create a cross-table of the two categorical variables consisting of \n",
        "  # percentage of observations that belong to the pair of categories \n",
        "  table = pd.crosstab(index=data[ind_var], columns = data[dep_var]).apply(lambda r: r/r.sum(), axis=1)\n",
        "  \n",
        "  # plot this cross-table as a stacked  bar graph \n",
        "  table.plot(kind='bar', figsize=(10,4), stacked = True,alpha=0.8)\n",
        "  title = 'Stacked bar plot of ' + dep_var + ' versus '+ ind_var \n",
        "  plt.title(title, loc = 'center')\n",
        "  plt.ylabel('Percentage')\n",
        "  plt.legend(loc=3, bbox_to_anchor=(0., 1.02, 1., .102) ,ncol=2, mode=\"expand\", borderaxespad=0.)"
      ],
      "execution_count": 0,
      "outputs": []
    },
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          "height": 365
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        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271146435,
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          "elapsed": 1246,
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      },
      "cell_type": "code",
      "source": [
        "stacked_plot(adult_train, 'workclass','income')"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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G5s2b0bVrV0ybNg2PHj0qdT9RVaWzI19E2nb//n2kpaWhY8eOAIB69eph7NixiI6Oxj//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\nLxEREZEc+g8pzbi0iRVxbQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41c630550>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "FeaGGIp7RMyB",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "1. From the above plot we can observe that there is a large proportion of the Self Employed People who earn more than 50K.\n",
        "2. At the same time bigger proportion of the Federal Government, Local Government, Private State governemnt employees earn less than 50K."
      ]
    },
    {
      "metadata": {
        "id": "FFt2rpP-RJyp",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 353
        },
        "outputId": "4eabbc0c-d34c-40d7-ad94-b85d13f6b54c",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271180169,
          "user_tz": -60,
          "elapsed": 989,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "stacked_plot(adult_train, 'education','income')"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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LKP7fp7jnJ/97QEdHp0D3N5G2YfFFpKIXL14gJiYGrVu3BgBUrlwZo0ePRnBwMO7fvw8j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\nJEWp5aijew9P7devH4C7d3DJecwPG6+/p6ZgUzX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            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41b11ec90>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "gifp-JpxRSux",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "1. From the above plot it can be observed that the extremely large proportion of the people who have not attended the university earn less than 50K. \n",
        "\n",
        "2. Also, as the years of education gets higher and higher the proportion of people earning more than 50K increases."
      ]
    },
    {
      "metadata": {
        "id": "NeCmZRNVRSFw",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "outputId": "36f14172-7b7b-4110-ce8f-35f3eb782d8a",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271202134,
          "user_tz": -60,
          "elapsed": 1056,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "stacked_plot(adult_train, 'marital-status','income')"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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zc3MkJiaiXLlymD9/PqKiotCiRQtMmjSpwAyVKpWFRmOi7+t6I1NN8V9ZqTjb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\nijQ6fQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41bc3b6d0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "MXRrRbacRaiC",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "1. Interestingly very small proportion of divorced, windowed, separated, never married people earn greater than 50K.\n",
        "\n",
        "2. At the same time nearly 50% of Married-AF-Spouse and Married-civ-spouse earn more than 50K."
      ]
    },
    {
      "metadata": {
        "id": "q_sqMcOTRXb3",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "outputId": "4b776f4c-c297-48ec-c3ba-0361440ed425",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271229658,
          "user_tz": -60,
          "elapsed": 2529,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "stacked_plot(adult_train, 'occupation','income')"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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VKlXC/fv3xeXW1tbaRCEiIiL6rGnV8jVq1CgolUpERESgQYMGuHLlCoYMGZLn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\ncej1etzc3NDr9WzatIno6Gjmz59fpNfV6EVsqvL/KDU1lV2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YmZkxdepULC0t6dOnD/v3\n7wdg4cKF5OTkMHbsWJydnRk+fDiJiYlkZmYSEhKCk5MTP/74I8uWLcPCwoLc3FzCwsK4d+8ea9as\nwcrKilKlSnHo0CE8PDzo0aMHmzZtYsOGDZQuXZry5csza9YsrKys8PDwYNiwYRw4cIB79+7x9ddf\nU6tWLZWfTUmSRCG3HSVJEtKJEyfYvXs3a9euZd26dTx69IiYmBiWLFnCunXr2LhxIykpKSQnJ/PV\nV1/RqlUr1q9fz6hRo9i2bdsLf3dubi6Ojo5ERUXxySefsGDBAgDS09OZP38+UVFRtGrVirVr19Kg\nQQNatmzJ4MGD6dSpk/I7bt++zcKFC1m5ciVRUVFUqlSJlStXApCRkYGTkxOrV6/Gx8eH77//vsie\nJ0mSTI9c+ZIkSUgnT56kUaNGSnNVT09PIiMjqVu3LqVKlQIgJCQEyOuEP2DAAOW/8/T05ObNmy/8\n/S1atADA3d2dyMhIACpUqEBgYCB6vZ579+7RoEGD5/75s2fPUrduXWXAt6enJxs2bFB+3qRJEwDs\n7Oy4du3a//z/L0nS60smX5IkCenZQd+GkUeFHVPVaDTodLoX/vns7Gyjx/L/Ho1GQ3Z2NmPGjGHr\n1q1Ur16dNWvWkJSU9NLxGuIzMDMzK/RakiRJcttRkiQhubm5kZiYSHZ2NgBHjhxh4MCBnDp1ioyM\nDABGjx5NUlISDRo04MCBAwAcO3aMwMBArKysSEtL488//yQ3N5dffvnF6PcfPXoUgOPHj1OrVi0y\nMzPRarVUrlyZp0+fsmfPHrKysoC/krP8XFxcOHPmjBLL4cOHqV+/ftE9IZIkvTbkypckSUKqX78+\nPj4+9O3bF61WS926dfnoo4/Iycmhf//+mJub4+7ujouLC5UqVSIoKIiEhAQA/v3vf1O2bFm6dOlC\nt27dqFq1Ks7Ozka//+zZs6xfv560tDRCQ0OxtramY8eOdO/eHTs7OwYNGsSECROIi4ujSZMmhIWF\nGa1g2draMnr0aAYMGICFhQW2trZ8/vnnxfocSZJkmmSrCUmS3ji1atXizJkzmJvL+09Jkoqf3HaU\nJEmSJEkqRnLlS5IkSZIkqRjJlS9JkiRJkqRiJJMvSZIkSZKkYiSTL0mSJEmSpGIkky9JkiRJkqRi\nJJMvSZIkSZKkYiSTL0mSJEmSpGL0f3M+z42NGBG0AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41c4f0650>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "fEwg52GKRh2G",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "1. Larger proportion of executive managerial people and professors earn more than 50K while very small proportion of people belonging to farming, cleaning, machine handling, admin and Arm forces earn more than 50K.\n",
        "\n",
        "2. There is significant proportion of people in sales, technology and transport who earn more than 50K."
      ]
    },
    {
      "metadata": {
        "id": "KNS4fN6vRdy2",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 325
        },
        "outputId": "cc19017b-64b1-473e-fc4d-6cf7a5a62243",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271259500,
          "user_tz": -60,
          "elapsed": 1245,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "stacked_plot(adult_train, 'gender','income')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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A0wYNGigiIkLdunVzaGEAAADuqMier6+//lpTp07VsWPHbJ7BlZOTo7Jlyzq6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\nQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41c3d6190>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "06_89ygXRn8h",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "1. Men seems to be earning significantly more than women, of pay more than 50K. \n",
        "2. There is a bigger proportion of female who earn less than 50K than the male."
      ]
    },
    {
      "metadata": {
        "id": "gPLL_zqBRlZL",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 353
        },
        "outputId": "990415f0-bca8-4c36-e62c-213aa57c6660",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271283797,
          "user_tz": -60,
          "elapsed": 499,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "stacked_plot(adult_train, 'relationship','income')"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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zfoa+uTKFr0GDBsHd3R2JiYlQKpWoW7cusrOzUa9evdfuY2FhgfT0dGH50aNH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\nIiIJ/T+xB5ZYBRz1+AAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41c35c1d0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "L-O_iYL6RwLV",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "1. Roughly 50% of the people earn more than 50K who call themselves as husbands and wives. \n",
        "\n",
        "2. A very small proportion of people who are not in a family or are unmarried earn more than 50K."
      ]
    },
    {
      "metadata": {
        "id": "2JngB-KjRrgc",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 382
        },
        "outputId": "06801078-e0d9-455b-cf92-355c9c3b23e1",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271313923,
          "user_tz": -60,
          "elapsed": 671,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "stacked_plot(adult_train, 'race','income')"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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C0wYNGqht27bq27evU4MBAAAURQWOfK1YsUJRUVFKTEzMNweXzWaTn5+fs7MB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\nAMBA/wce47yppNtiPwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41c2455d0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "u3YhB1hXR2nj",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "1. Significanly larger proportion of Asian and White peole earn more than 50K than other races. \n",
        "\n",
        "2. Relatively very small fraction of the Black and Other races earn more than 50K."
      ]
    },
    {
      "metadata": {
        "id": "gzF8P0ScRy0a",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "a5473292-6050-4551-ab38-a7fb17498934",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271345083,
          "user_tz": -60,
          "elapsed": 1032,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "stacked_plot(adult_train, 'native-country','income')"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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mseWLiIiIyIjeqpYvenvwJ6GIiKis0jn5kslkePr0KWrXrm3I+lAFxS5fIiKi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\nOXIE33//PRo1agSZTIaHDx9i2rRpWs8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//hv79+8vk/jKVRot5IomNzcXkZGRePXqFebO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\nQogBUfBFCCGEEGJA/w9ZVcoZL/Ec5QAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41c366510>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "r3AFBK-HR9Qc",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "1. Interestingly, a larger proportion of people from France, India, Iran and Taiwan earn more than 50K. \n",
        "\n",
        "2. Some countried like Columbia, Dominican Republic, Holland, Mexico and Nicaragua have very small proportion of peole who earn more than 50K."
      ]
    },
    {
      "metadata": {
        "id": "ge2YiYSNR6Ur",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 432
        },
        "outputId": "7a177bb7-72f8-4edc-833a-d60520225781",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271370623,
          "user_tz": -60,
          "elapsed": 554,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "import seaborn as sns \n",
        "\n",
        "sns.boxplot(x = 'income', y = 'age', data=adult_train)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python2.7/dist-packages/seaborn/categorical.py:454: FutureWarning: remove_na is deprecated and is a private function. Do not use.\n",
            "  box_data = remove_na(group_data)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fb41c358cd0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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T0tFLvsrLyyVJ4XBYY8eO1ahRozRy5Mi4vx/8OIQ2AACWYHocAABLENoAAFiC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\n/h/61GecGzUxUQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41c2f8a10>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "gWbkjLNtSDMx",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "> From the above plot it is evident that relatively older peole tend to earn more than 50K. This is due to the fact that the median age of pople earning less than 50K is less than the median age of peole earning more than 50K."
      ]
    },
    {
      "metadata": {
        "id": "Fsj2BgzYSAsI",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 378
        },
        "outputId": "febacd1f-d79c-4d71-e15d-1ffcbe41c8a9",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271395330,
          "user_tz": -60,
          "elapsed": 454,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "sns.boxplot(x = 'income', y = 'education-num', data=adult_train)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fb41c4451d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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s8oXzUlpaWuNZ3jt37tTUqVPl8XjkcrmUkZGhdu3aaevWrZo9e7Yk6bbbbtND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\nQ/wfSrkNbEDMKQMAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41c40a610>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "yV_Sv4lJSJd4",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "> As expected, the median age of people earning more than 50K is larger than the median age of people earning less than 50K. We should expect people with more years to education to earn more than people with less years of education."
      ]
    },
    {
      "metadata": {
        "id": "tHxnZe1BSGup",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 918
        },
        "outputId": "40bd6b18-fe8f-46ca-c795-d909571b8774",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271432435,
          "user_tz": -60,
          "elapsed": 8479,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "sns.pairplot(adult_train[['age','fnlwgt','education-num','capital-gain','capital-loss']])"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x7fb41c203690>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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3YZUJw81E0WbWQALg3to2hrpbkErn8M5H5bFJ54btcDMRwdrwoG6iZKN+8qhV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5ZweMSMOWe4xprOqqcsg/gE8O41JxMUjvbqYNI1Plu5fAHf/tE1fPP393zsft5Pum/wk0Qr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\nhwWhfUn1AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb41c2035d0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "ura2zX6hSSeh",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "From the above pairplot of the numeric variables we can observe that :\n",
        "\n",
        "1. No two pairs of the numeric variables shows strong dependence among themselves.\n",
        "\n",
        "2. Age, fnlwgt and capital-gain variables are skewed to the right while education-num is skewed to the left. \n",
        "\n",
        "### Some more data pre-processing"
      ]
    },
    {
      "metadata": {
        "id": "1Z5PIFTgSN2F",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 561
        },
        "outputId": "36f3db2b-f30c-4c26-e73a-d5b975cfffc9",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271465840,
          "user_tz": -60,
          "elapsed": 485,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# Lets check the unique values of \n",
        "print adult_train.apply(lambda x: len(x.unique()))\n",
        "print adult_test.apply(lambda x: len(x.unique()))"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "age                  72\n",
            "workclass             7\n",
            "fnlwgt            20263\n",
            "education            16\n",
            "education-num        16\n",
            "marital-status        7\n",
            "occupation           14\n",
            "relationship          6\n",
            "race                  5\n",
            "gender                2\n",
            "capital-gain        118\n",
            "capital-loss         90\n",
            "hours-per-week       94\n",
            "native-country       41\n",
            "income                2\n",
            "dtype: int64\n",
            "age                  73\n",
            "workclass             7\n",
            "fnlwgt            11913\n",
            "education            16\n",
            "education-num        16\n",
            "marital-status        7\n",
            "occupation           14\n",
            "relationship          6\n",
            "race                  5\n",
            "gender                2\n",
            "capital-gain        110\n",
            "capital-loss         79\n",
            "hours-per-week       89\n",
            "native-country       40\n",
            "income                2\n",
            "dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "iAK1VoQcSapi",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "> From the above result it can be observed that the native-country in the train set has one extra level than the test set. From the analysis below it is clear that 'Holand-Netherlands' is not present in the test set."
      ]
    },
    {
      "metadata": {
        "id": "_BVL9tG_SX8s",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "outputId": "21a40dd2-39b5-4f21-f699-0bb221265267",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271490390,
          "user_tz": -60,
          "elapsed": 516,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# print unique country levels in the training set \n",
        "print (adult_train['native-country'].unique()) , '\\n'\n",
        "\n",
        "# print unique country levels in the set set \n",
        "print (adult_test['native-country'].unique()), '\\n'\n",
        "\n",
        "# lets check what levels of the native country variable are not present in the test set \n",
        "set(adult_train['native-country'].unique()).difference(set(adult_test['native-country'].unique()))"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['United-States' 'Cuba' 'Jamaica' 'India' 'Mexico' 'Puerto-Rico'\n",
            " 'Honduras' 'England' 'Canada' 'Germany' 'Iran' 'Philippines' 'Poland'\n",
            " 'Columbia' 'Cambodia' 'Thailand' 'Ecuador' 'Laos' 'Taiwan' 'Haiti'\n",
            " 'Portugal' 'Dominican-Republic' 'El-Salvador' 'France' 'Guatemala'\n",
            " 'Italy' 'China' 'South' 'Japan' 'Yugoslavia' 'Peru'\n",
            " 'Outlying-US(Guam-USVI-etc)' 'Scotland' 'Trinadad&Tobago' 'Greece'\n",
            " 'Nicaragua' 'Vietnam' 'Hong' 'Ireland' 'Hungary' 'Holand-Netherlands'] \n",
            "\n",
            "['United-States' 'Peru' 'Guatemala' 'Mexico' 'Dominican-Republic'\n",
            " 'Ireland' 'Germany' 'Philippines' 'Thailand' 'Haiti' 'El-Salvador'\n",
            " 'Puerto-Rico' 'Vietnam' 'South' 'Columbia' 'Japan' 'India' 'Cambodia'\n",
            " 'Poland' 'Laos' 'England' 'Cuba' 'Taiwan' 'Italy' 'Canada' 'Portugal'\n",
            " 'China' 'Nicaragua' 'Honduras' 'Iran' 'Scotland' 'Jamaica' 'Ecuador'\n",
            " 'Yugoslavia' 'Hungary' 'Hong' 'Greece' 'Trinadad&Tobago'\n",
            " 'Outlying-US(Guam-USVI-etc)' 'France'] \n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Holand-Netherlands'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "metadata": {
        "id": "Dz_2Mf_LSd77",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "c9e2c4d2-5ae7-4f9a-9b5f-c478f7b6a5a0",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271500966,
          "user_tz": -60,
          "elapsed": 618,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# meger the train and the test data set \n",
        "adult_full = pd.concat([adult_train,adult_test])\n",
        "\n",
        "# print the dimensions of the three data sets just for checking \n",
        "print adult_train.shape\n",
        "print adult_test.shape\n",
        "print adult_full.shape"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(30162, 15)\n",
            "(15060, 15)\n",
            "(45222, 15)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "38FU35n_Sgfi",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "830ca261-08c7-4e6e-e782-49e4dd182fc3",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271511519,
          "user_tz": -60,
          "elapsed": 643,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# print the unique levels of the income variable \n",
        "print adult_full.income.unique()\n",
        "\n",
        "# looks like the test set levels has been corrupted by a dot \n",
        "# therefore we recode them and then replace then my 0 and 1 in the merged data\n",
        "\n",
        "encode = {'<=50K':0, '>50K':1, '<=50K.':0, '>50K.':1}\n",
        "\n",
        "# Lets replace level code by 0 and 1 in the full data set\n",
        "adult_full =  adult_full.replace(encode)\n",
        "\n",
        "print adult_full.income.unique()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['<=50K' '>50K' '<=50K.' '>50K.']\n",
            "[0 1]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "rEianckESmKZ",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### Building Classification Algorithms"
      ]
    },
    {
      "metadata": {
        "id": "huHuJTIISjEB",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# change the categorical columns to binary using dummy variable (often called one-hot encoding) \n",
        "\n",
        "one_hot_columns = ['workclass','education','marital-status','occupation','relationship','race','gender','native-country']\n",
        "\n",
        "adult_full_oh = pd.get_dummies(adult_full, columns =  one_hot_columns, drop_first=True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "m96JDcaLSpZJ",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "2fa38b24-ad38-4fbf-ce75-342cbfa45604",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271547441,
          "user_tz": -60,
          "elapsed": 428,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# lets re-divide the full dataset according to the shape of the \n",
        "# old trainning and test set\n",
        "adult_train_new = adult_full_oh.iloc[:len(adult_train)]\n",
        "adult_test_new = adult_full_oh.iloc[len(adult_train):]\n",
        "\n",
        "# print the shape of new train and old train dataset \n",
        "print len(adult_train_new)\n",
        "print len(adult_train)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "30162\n",
            "30162\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "vJUmN0mTSr4n",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# set the independent and dependent variables\n",
        "\n",
        "dep_var = 'income'\n",
        "\n",
        "ind_var = [x for x in adult_train_new.columns if x not in [dep_var]]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "4surG99-SvPv",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "#### Logistic regression "
      ]
    },
    {
      "metadata": {
        "id": "h7m6sFn1SukY",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LogisticRegression\n",
        "\n",
        "model = LogisticRegression(fit_intercept = True, C = 1e9).fit( adult_train_new[ind_var],adult_train_new[dep_var])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "qAmgYlDVS45p",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "##### A function to plot the confusion matrix "
      ]
    },
    {
      "metadata": {
        "id": "lZ9ROsXBS0ue",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          }
        }
      },
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import confusion_matrix\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def plot_confusion_matrix(y_true, y_pred, xticks = ['<=50K', '>50K']):\n",
        "  \"\"\"\n",
        "  Function to plot the confusion matrix of a binary classification model\n",
        "  Input :\n",
        "  -------------------------\n",
        "  y_true - true y labels \n",
        "  y_pred - predicted y labels \n",
        "  \n",
        "  Output :\n",
        "  -------------------------\n",
        "  Simply plots the confusion matrix of a binary classification problem\n",
        "  \"\"\"\n",
        "  # create the confusion matrix of the true and predicted labels \n",
        "  cm = confusion_matrix(y_true, y_pred)\n",
        "  # convert them to a data frame \n",
        "  df_cm = pd.DataFrame(cm, range(2), range(2))\n",
        "  # plot the confusion matrix of the above classification model as a heatmap\n",
        "  sns.set(font_scale=1.4) \n",
        "  ax = sns.heatmap(df_cm, annot=True, fmt='g',annot_kws={\"size\": 16}, \n",
        "              xticklabels = xticks, yticklabels=xticks).set_title('Plot of the confusion matrix')\n",
        "  plt.xlabel('Predicted Labels')\n",
        "  plt.ylabel('True Labels')\n",
        "  plt.show()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "0G2HGonkS8CV",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "outputId": "79c8c962-1992-4280-eb77-d1849b6ddec1",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271625035,
          "user_tz": -60,
          "elapsed": 765,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "# predictions on the test set \n",
        "\n",
        "predictions = model.predict(adult_test_new[ind_var])\n",
        "\n",
        "#plot the confusion matrix\n",
        "\n",
        "plot_confusion_matrix(adult_test_new[dep_var], predictions)"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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0OSZtIiJSa5yIJsekTUREak2DSVuGYw5EREQVBJM2ERFRBcHhcSIiUmsi9i9lmLSJiEit\ncSKaHJM2ERGpNU5Ek2PSJiIitcaHq8jxQgEREVEFwaRNRERUQTBpExGRWtMQaZR4KY7o6Gj07t0b\nXbp0USj/559/MHDgQDg6OqJnz57YuXOnQv327dvxxRdfwNHREQMHDkRISIisTiqVYu7cuejUqROc\nnZ3h7e2N+Ph4Wf2zZ8/g7e0NZ2dndOzYEfPmzYNUKv3wuSjWEREREZUTkUhU4uVDjh49itGjR6NB\ngwYK5YmJifD29oarqysuXbqERYsWISAgAOfPnwcAnD17FitWrMD8+fNx+fJluLm5wcvLCy9evAAA\nBAYG4ubNmwgKCsKpU6dgbGyMCRMmyNr38fGBsbExTp48iR07duDmzZtYvXr1B+Nl0iYiIrWmIRKV\nePmQ9PR07N69G61bt1YoP3ToEMzNzTF48GDo6enB0dER/fr1w65duwAAO3fuRP/+/dGyZUvo6urC\n3d0ddevWxZEjR5CdnY29e/di3LhxsLCwgIGBAfz8/BAaGorIyEiEhYXhzp078PPzg6GhIczNzeHl\n5YU9e/YgNze36HNR8tNIRESkfKJS/PchX331FerVq5evPCIiAs2aNVMos7GxQVhYmKzexsamwPrY\n2FikpqYq1JuYmKBOnToICwtDREQE6tatCxMTE1l9s2bNkJycjNjY2CLjZdImIiJ6j0QigaGhoUKZ\nkZERkpKSCq0Xi8WQSCSQSCSyz+/XJyUlFbotAFn7heF92kREpNbK633agiAobfuSts2kTURE9B5j\nY2NZjzlPUlISTE1NZfXv94olEglMTExkw97v96jz6gVByNd23ue89gvD4XEiIlJrypw9XpjmzZsj\nPDxcoSwsLAx2dnYAAFtb23z1oaGhsLe3h4WFBcRisUJ9QkIC4uPjYW9vD1tbWyQkJCAxMVFhW1NT\nU1hYWBQZF5M2ERGpNWXOHi9M3759kZiYiO3btyMzMxNXr17F4cOH4enpCQDw8PDAoUOHEBISgszM\nTGzduhXJycno3bs3NDU14e7ujvXr1+Px48dISUnB0qVL4eLiAktLS9jY2MDe3h7Lli1Damoq4uLi\nsH79enh4eHzwi4ZIKO2gfTlp0aBjeYdAVGohYQfKOwSiMqFjWPSwbmn0sfMo8baHb28vsr5Hjx54\n+vQpcnNzkZ2dDR0dHQDA8ePHER8fj4ULF+LevXswMzODj48PXF1dZdvu2bMHGzZsQGJiIpo0aYIf\nf/wRLVq0AABkZWVhyZIlOHz4MKRSKdq2bYt58+bJhs4TEhLg7++PK1euQE9PD/3798eUKVOgqalZ\nZLxM2kTliEmbKouKmrQrGk5EIyIitcb3acsxaRMRkVrj+7TlOBGNiIiogmBPm4iI1FpxHkdaVTBp\nExGRWiuvJ6KpI54JIiKiCoI9bSIiUmucPS7HpE1ERGqNs8flmLSJiEitcSKaHK9pExERVRDsaRMR\nkVrj8Lgce9pEREQVBHvaRESk1jh7XI5Jm4iI1BqHx+WYtImISK1x9rgckzYREak19rTlOBGNiIio\ngmDSJiIiqiA4PE5ERGqNs8flmLSJiEit8Zq2HJM2ERGpNc4el2PSJiIitcaethwnohEREVUQTNpE\nREQVBIfHiYhIrXH2uByTNhERqTVe05Zj0iYiIrXGnrYckzYREak13vIlx4loREREFQR72kREpNY0\n2NGWYU+biIiogmBPm4iI1BonoskxaRMRkVrjLV9yTNqVjEgkwrffDcfYCUOxcdV/sX7lVlmdhoYG\nfL4fhT5f9YCxsRj37/2LFYs24OrF67J1TEyN8P2s8ejQxQU6Otq4cS0Mi2evROy/TwAALV3s8dvu\nVQXu2733WNwJiwYAtOvkjDG+nrBq8hkEQcDt6+EI/Gkj7kbeV97BU5WUlvYa/QYOgpaWFk4cOiAr\n37ZjF3bs3ofniYn4xLwevEePQK8e3QEA167fwEhvn0LbDLt2SelxU/Gxpy3HpF2JGBmL8dPqH2Fu\nURe5ubn56idOG4v+3/TCnGnL8PB+LPq4dcfaLT/BvfdYxNx9CA0NDawPCoCBgT78xs9F/LPnmDbb\nB5u2r4Br16F48yZT1tagPl6If/ZcoX3Jq2QAgGOrFlj1yyL8d+Mu/Pj9YoiNDDHN3xdrty6Ba9eh\neJ2WrtwTQVXKmg0b8SpJgtq1asrKdu3dj1VrN+DH6X6wa26L4EtXMGP2PIgNDdG2tQvsWzTHmWOH\n87UVsGoNEl+8UGX4RB+FE9Eqkd79/4OcnBwM7uuFnOwchTr9GtUxaLgbNq3ehtMnLuBhzCOsXroZ\n92MeYbiXOwCgVWt7NG1miYWzAnElOAT/3o+Fn89cGJuI0dutu0J7Sa8keJn4SmHJyXm7z/982Qlh\nt+5g9bLNiP33CcJuRWLZgrUwq1MLdo7NVHMyqEqIuBOJA38eRq8e/5GVCYKAzVu3YaCbK1z7fIlP\nGzaA5+Bv0KlDO2zesg0AoK2tjZo1TRWWVxIJTpw6jSnf+ZbX4VAhNCAq8VLZMGlXImdOBsNnxHSk\npqTlq3No2Rx6erq4dOGaQvmVCyFwad8SANDIsiEA4MY/obL6tNTXuP5PKFzatSx2HEvmrMbwrwr+\nw5eX2IlKKycnB3MXL8VwTw+Y16srK3/47yM8f56I1i5OCuu3dmqFm7dDFUaM3rV0xSr06tEdTa2t\nlRo3fTyRSFTipbJh0q5EnsTFQxCEAussGpoDAJ7GxSuUP459itpmNVGtmh40Nd7+OuS8N7Se9FIC\niwb1ShyXuUUdTPAbg9s3InDt8q0St0P0rp179iE9PR1jRgxVKI+NewwAMK9bV6H8E3Nz5Obm4vGT\nJ/naunU7DNeu38jXFpG6UVnSTkhIKLI+Ozsbs2fPVlE0VY++fnXk5ubm62Wkp2e8rTeojn8fxAEA\nmtpaKqxj2aQRqutXVygbMvIr7D32K87dPIigP9YV2BPv0KU1/on+G8eCd+PliyR4e04p8Fo70cdK\neJ6Inzduxg9Tp0BHR0eh7nX62zkT1arpKZRXr14NAJD2+nW+9n7dFoROHdqhYYP6SoqYSkNDJCrx\nUtmoLGkPGjQIcXFxBdYlJSVh+PDhOHfunKrCoQJcvhCC2H8fY+psX5jVrQUdXR2MmzwSdc3NkJ2d\nDQDIyspC4vOXyMrKxmy/JZgweiaexD3DhqBlaNXaQaG9a5dvYuAXozB+xDTUb2iOTdtX5PtDSlQS\nPwUEolP7dmjt3KrUbT199gznLlzEoK+/KoPISBlEopIvlY3Kknbv3r0xaNAg3Lt3T6E8OjoaAwYM\nQE5ODvbt26eqcKqc1NQ0aGhooLp+NYXyGgb6AIC0lNfIycmBz8gZqFZNFyev7MOlsL9Qu05NHNx3\nHEkvJQCA29cj0LWVGwIXb0Bk+F3cvh6Bmd8txL8P4jDGZ4hC2xkZb/DvgzhcOH0F3p5+sGzSCAMG\n91HNAVOlde7CRVy/eQt+kyYUWG9Q43+/068V71JIS0v7X30NhfIz5y5Av3p1fO5or4RoicqWym75\nmjx5MoyMjODp6YnNmzejefPmOHnyJKZOnYq+ffti1qxZ0NbWVlU4VU7sw7fX+SwamCP6ToysvEHD\nT/D0cbxs2Pzf+7Fw6z4Ctc1qIjX1NTLSMxC4cQHuRj0otO3c3FzERD9EI8sGAN7eo530KhkRoVGy\ndSRJyXiZ+AoNG1ko4/CoCjl5+gwkycno2qufrCw3NxeCIMDepT28Ro0AAMQ9fgyrxp/J1nkU+xha\nWlqw+MRcob0z54Ph4tQK2lq8A1ZdVcZh7pJS6W/pyJEjIRaLMXr0aPTo0QOHDh3CDz/8gK+//lqV\nYVRJN6+FIf11Otp2dFJI2u06OSP4zFUAb28L69K9Pa5evI7nCW/vVRUbGaJ1+88xccwsAEC/r79A\nY6uGWL5wvawNDQ0NWDX9DPfv/gsAGO0zBEKugBED5T0hQ7EBapvVlLVLVFK+33phmMcghbLd+w7g\nzPkL2LA6ECYmxjj011FcvHwVXTt1lK1z/uIlOLdqqXANPCcnBzdvh8LXe6zK4qePx1dzyqn8q+WA\nAQMgFosxefJkTJ8+nQm7DBmKDaCtIx+tqK5fDaa1TAC8nQG+ZcMujPx2MO7f/Rcxdx9gyMivUbtO\nTWzZuBMAIJVmYeL0sbgX9QDLF6yDppYm/Gb7IPTmHdlT0169TILn6KkQBAF/7DkGLU1NeI4eiE/q\n14W/3xIAwNYNO7H618WYPNMbf+w5Bj09XUyYOgZSaRaOHPhbxWeFKhuz2rVgVruWQpmJiTG0tLRg\n+b+e9bdjRsF/wWLYt2iOlo72OPb3KVy7fgNbN65T2C4+4TmkUinMzRVnmpN6qYy3bpWUypL2u5PM\ntLW1MXjwYKxfvx516tSBpqamrK5jx44FbU7FELhxvsJksGFj3TFs7NsHp/Rs+w02rdkGDQ0RZi2a\nDCMjQ0TfiYGX5xQ8iXsGAMiSZmH88GmYOtsHv/+5DlJpFk4ePYcVi+S96gunr+D7b2dj5Lce+Gpw\nX2hqaiAy/B6+HToVN0PCAABnT13CVJ+5GO7ljkHD3JCW+hrhoVEYOmA8nj5WvOWMSBn6fvkF0tPT\nsW7Tr3iemIgG9S2wculi2Ns1V1gvJTUFAKCvr18eYRJ9NJFQ2I29ZaxJkyYfXEckEiEyMrJY7bVo\nwOROFV9I2IEPr0RUAegYmiqt7Vk9Z5Z42wXHFxVZHxkZiZ9++gl37tyBlpYWWrVqhenTp6NevXr4\n559/EBAQgJiYGNSuXRvDhg3DoEHySzPbt2/H77//joSEBDRu3BhTp05Fy5Zvb3+VSqVYvHgxzpw5\ng4yMDDg4OGDOnDmoU6dOiY8FUOHs8aioqA8uxU3YRERUdSjrlq/s7GyMGTMGzZs3x8WLF/H3328v\n302ZMgWJiYnw9vaGq6srLl26hEWLFiEgIADnz58HAJw9exYrVqzA/PnzcfnyZbi5ucHLywsv/vfs\n+sDAQNy8eRNBQUE4deoUjI2NMWFCwXc8fAyVPxFNIpHg8uXLOHr0KI4ePYqrV6/KbsUgIiJSlWfP\nniExMRH9+/eHjo4ODAwM0KtXL0RGRuLQoUMwNzfH4MGDoaenB0dHR/Tr1w+7du0CAOzcuRP9+/dH\ny5YtoaurC3d3d9StWxdHjhxBdnY29u7di3HjxsHCwgIGBgbw8/NDaGhoqTunKrumnZaWhtmzZ+PE\niRMQBEF2Den169fQ1NSEq6srZs2aBV1dXVWFREREFYCybvkyNzdHkyZNsGvXLkycOBEAcPToUXTp\n0gURERFo1kzxBUc2NjY4efIkACAiIgI9evTIVx8WFobY2FikpqbCxsZGVmdiYoI6deogLCwMTZs2\nLXHMKutpz507FykpKdi9ezdCQ0Nx7do1XLt2DaGhodi2bRsePXqE+fPnqyocIiKqIESl+K8oGhoa\n+Pnnn3H69Gl8/vnn+Pzzz/H06VP4+/tDIpHA0NBQYX0jIyMkJSUBQIH1YrEYEokEEolE9vn9+rzt\nS0plSfvy5ctYunQpbG1tofXOQwy0tLTg4OCA5cuXy64nEBER5VHWs8elUim8vb3Ro0cPhISE4Pz5\n86hduza+//57ACj0BUzFpYx53mrzli9NTU2+TIKIiFTm8uXLePToESZNmgQDAwOYmZlhwoQJOH/+\nPDQ0NGQ95jxJSUkwNX07S97Y2Dhfr1kikcDExAQmJiayzwXVl4bKkrazszOmTp2KqKgohW8fOTk5\nCA0NhZ+fH7p06aKqcIiIqIJQ1uzxnJycfL3hvJcjOTk5ITw8XKEuLCwMdnZ2AABbW9t89aGhobC3\nt4eFhQXEYrFCfUJCAuLj42FvX7pn3Kssac+ZMwfVq1eHm5sbmjdvDmdnZzg5OaFFixYYNGgQjI2N\n4e/vr6pwiIioinNwcECNGjWwcuVKpKenIykpCRs2bICDgwO++uorJCYmYvv27cjMzMTVq1dx+PBh\neHp6AgA8PDxw6NAhhISEIDMzE1u3bkVycjJ69+4NTU1NuLu7Y/369Xj8+DFSUlKwdOlSuLi4wNLS\n8gNRFU1lD1fJ8/LlS0RGRsqGDUxMTNC0aVMYGxt/VDt8uApVBny4ClUWyny4yoI+s0u87azD84qs\nDw8Px5IlSxAVFQVtbW20atUKM2bMQJ06dXD9+nUsXLgQ9+7dg5mZGXx8fODq6irbds+ePdiwYQMS\nExPRpEkT/Pjjj2jRogWAt6+NNSGCAAAgAElEQVQxXrJkCQ4fPgypVIq2bdti3rx5pR4eV3nSzvPq\n1SucOnUKz58/h4WFBbp3745q1ap9eMP/YdKmyoBJmyoLZSbtRX1LPgo789DcMoyk/KnsPm1HR0fc\nuHEDAHDz5k2MHj0a1atXR926dREbG4uAgABs27YNn376qapCIiKiCoDvC5FT2TXtvIv7ADB//nx4\neHjg3Llz2LNnDy5cuIAvvvgCc+bMUVU4RERUQSjrlq+KSGVJ+91Xqz169AjffvstNDTe7l5bWxsT\nJ05EaGioqsIhIiKqcMrlPm1LS8t896+lpaXx9XhERERFUNk17aysLMyYMQPA26fQBAQEYPny5QCA\n6OhozJs3Dx06dFBVOEREVEF86HGkVYnKkna/fv1k/7a2toaFhYXs8x9//AFjY2NMnz5dVeEQEVEF\nIaqE16ZLSmVJe/HixYXWMVkTEVFhNJizZVR+TXv27NlFfiYiInqXSCQq8VLZqDxpHzx4sMjPRERE\nVDCVJ+33H8BWTg9kIyIiqnBUdk07z/vDFZVx+IKIiMoO84ScypM2ERHRx+BENDkmbSIiUmvsacup\nPGnzmjYREX0M5mw5lU5EO336NObNU3y36fHjxxEREYHt27erMhQiIqIKR6VJ28zMDMuXL0dWVpas\nrF69eli9ejW0tDhST0RE+fEtX3IqTdrNmjVDw4YNcfjwYVlZTEwMbt++DVdXV1WGQkREVOGo/D7t\nYcOGYcuWLbLPW7ZswTfffANdXV1Vh0JERBWAqBT/VTYqT9pdu3aFVCrFhQsX8OLFCxw7dgxDhgxR\ndRhERFRBiEQlXyqbcnm4ytChQ/Hrr7/C3t4e3bp1Q61atVQdBhERVRCV8dp0SRWrp52Tk4O9e/fK\nPp87dw7jxo3D8uXLIZVKP3qnbm5uiIyMxLZt2zBy5MiP3p6IiKgqKlbSDgwMxC+//AIAePr0KXx8\nfJCamooTJ05g+fLlH73TatWq4ffff8evv/6KJk2afPT2RERUdfAtX3LFStp//fUXNm3aBAA4fPgw\nLC0tERQUhF9++QUnT54s0Y4tLS3h4OBQom2JiKjq4DVtuWIlbYlEggYNGgAALl26hJ49ewIA6tev\nj1evXikvOiIiIpIpVtI2NDTE48ePkZiYiJs3b6JNmzYAgOfPn/NWLSIiUioOj8sVa/Z4t27dMGjQ\nIGhoaOCzzz6Dra0t0tPTMWvWLLi4uCg7RiIiqsL4li+5YiXtadOmwczMDKmpqfDw8AAAaGhoQCqV\nYuHChUoNkIiIiN4qVtLW0dHB2LFjFcr09PSwdetWZcREREQkUxmHuUuq0KS9dOnSYjUgEong5+dX\nZgERERG9izlbrtCkffz48WI1wKRNRETKxCeiyRWatE+fPq3KOIiIiOgDiv3CkKysLFy+fBn79++X\nlaWnpyslKCIiojy85UuuWEk7Li4OPXv2xIgRI+Dv7w8AePz4Mbp164aYmBilBkhERERvFStpL168\nGA4ODrh06RI0NN5uYm5uDjc3NyxZskSpARIRUdXGx5jKFeuWr2vXruHUqVMQi8Wy4QaRSIRvv/0W\n7du3V2qARERUtVXGYe6SKlbS1tDQgL6+fr7y3NxcCIJQ5kERERHlYc6WK9bwuJWVFXbu3KlQlpub\ni3Xr1vHVmkREpFQaIlGJl8qmWD3tCRMmYMyYMfjjjz+QnZ2N0aNH4+7du0hJSZG9spOIiIiUq1hJ\nu1WrVti/fz92794NU1NT6OnpwdXVFYMGDULdunWVHSMRERGhmEkbAD777DPMnDlTmbEQERHlUwlH\nuUusWElbKpVizZo1+Pvvv/Hs2TPo6uqiTp066NOnD0aMGAFtbW1lx0lERFUUZ4/LFStpL1iwACdO\nnECvXr3QoEEDAMDDhw+xefNmJCQk4Mcff1RqkEREVHUxZ8sVK2n/3//9H7Zs2QIbGxuFcjc3N4wb\nN45Jm4iIlIY9bbli3fKVnZ0NS0vLfOXNmjWDVCot86CIiIgov2Il7Z49e+Lo0aP5yv/++2907969\nzIMiIiKi/AodHl+6dKns37q6uliwYAH27dsHa2traGhoICYmBuHh4Rg0aJBKAiUioqqJo+NyhSbt\n48ePK3w2MDDAkydP8OTJE1lZjRo1cOTIEUyaNEl5ERIRUZWm7Ceb/frrr/jvf/+LlJQU2NjYYN68\neWjcuDGio6OxcOFC3LlzB2KxGK6urvDx8ZFdYz9+/DjWr1+P2NhYWFhYwMfHRzb6LAgC1qxZg0OH\nDkEikcDGxgY//vhjgZeaP0ahSfv06dPFaiA1NbVUARARERVFmTl7165d2L17N3755ReYm5tj48aN\n2LBhAxYsWAAvLy/069cP69evx9OnTzFmzBjUrFkTgwYNQlRUFPz8/BAYGIj27dsjODgYkyZNwr59\n+2BlZYUdO3bgwIED2LhxIywsLLBp0yZ4eXnh2LFj0NXVLXG8xbqmXZiMjAz85z//KU0TRERERRKJ\nRCVePmTz5s2YOHEirKysoK+vj8mTJyMgIABnz55FRkYGfH19oa+vD0tLS3h6emLXrl0AgD179qBt\n27bo1q0bdHV10bVrV7Ru3Rp79+4FAOzcuRPDhg2DtbU1qlevjvHjxyM1NRUXLlwo1bko1i1fycnJ\nWLp0KW7evInMzEyF8ho1apQqACIiovKQkJCAx48fIz09HX369EF8fDwcHR0xd+5cREREwMrKClpa\n8jRpY2ODgIAAZGZmIiIiAu3atVNoz8bGBpcvX8abN28QExOjcJu0trY2rKysEBYWhm7dupU45mL1\ntBctWoSQkBC0adMG8fHx6NatG2rVqgVLS0v89ttvJd45ERHRh4hEJV+KEh8fDwA4cuQINm3ahGPH\njiErKwuTJ0+GRCKBoaGhwvpGRkbIzc1FcnJygfVisRhJSUlITk6GIAgQi8UF1pdGsZL2xYsXsW3b\nNsyaNQtaWlqYMWMGdu3aBTs7O4SEhJQqACIiovIgCAIAYNSoUahbty5q1qyJyZMn4/r168jOzpbV\nf2j7ktaXRLGSdkpKCszMzN5uoKGB3NxcAMDo0aP5ak4iIlIqZV3TrlmzJoC3Peg85ubmAIDExERI\nJBKF9SUSCTQ1NWFkZARjY+MC601NTWFkZAQNDY0C601MTEp8HoBiJu26deviypUrAAATExPcvHkT\nAKCnp4eXL1+WKgAiIqKiKGt4vE6dOjAwMMCdO3dkZY8fPwbw9jHd0dHRCk/9DA0NRdOmTaGjowNb\nW1uEh4crtBcWFgY7Ozvo6urC0tISYWFhsjqpVIqoqCjY29uX6lwUK2l7eHhg5MiRkEgk6NatGyZO\nnIjZs2djxIgRsLa2LlUARERERVFWT1tLSwuDBg3Chg0bcP/+fSQnJ2PlypXo1KkTunXrBiMjI6xZ\nswbp6emIiopCUFAQPD09AQDu7u64evUqTp48CalUimPHjiEkJATu7u4A3ubNoKAg3L17F+np6QgM\nDETt2rXRtm3bUp2LYs0eHzp0KMzNzSEWi/H9998jLS0N165dQ4MGDTB16tRSBUBERFReJkyYgIyM\nDAwePBiZmZno1KkT5syZAx0dHWzatAn+/v5wcXGBWCzG8OHD4erqCgBo3LgxAgMDsXz5ckyaNAkN\nGzbEmjVrZG/C/Oabb/DixQuMHDkSKSkpcHR0xMaNG0v9KmuRUMor5YIglMsbWFo06KjyfRKVtZCw\nA+UdAlGZ0DE0VVrbR79fW+Jtey0fX4aRlL9SPVwFQKnH54mIiIqizIerVDSlTtrKmNJORERE+RXr\nmnZRKuM3GSIiUh9MM3KlTtrl5djmH8o7BKJSy0pNLu8QiMqEMq9pK/stXxVJhU3aRERUNTBnyxWZ\ntCdOnPjBBrKzs8ssGCIiIipckUn71atXH2zA0dGxzIIhIiJ6H+dOyRWZtIOCglQVBxERUYGYs+VK\nfcsXERERqQYnohERkVoTabCrnYdJm4iI1BqHx+U4PE5ERFRBfHRPOzs7G1pa7KATEZFqcPa4XLF6\n2rm5uQgMDESHDh1kt3ilp6fD399f4QXhREREZU0kKvlS2RQraa9ZswZ//vknhg8fLivLyMhAaGgo\nVq1apazYiIiI+JavdxQraR88eBDr16/HyJEjZSfB1NQUK1aswMGDB5UaIBEREb1VrIvTr169go2N\nTb7y+vXrIzmZLzwgIiLlqYQd5hIrVk+7Xr16iIyMBKD4/uxLly6hVq1ayomMiIiIFBSrp923b1+M\nHz8eI0eOhCAIOHr0KO7cuYPdu3djxIgRyo6RiIiqMna1ZYqVtL28vJCVlYU1a9YgKysLkydPRs2a\nNeHt7c2kTURESlUZJ5SVVLGStkgkgq+vL3x8fPDq1Svo6uqiRo0ayo6NiIiIHe13FCtpx8TEFFnf\nuHHjMgmGiIjofXz2uFyxknbv3r2LHJ7Im6RGREREylOspL1t2zaFzzk5OXjw4AH+/PNPTJ48WSmB\nERERkaJiJW0nJ6d8Za1bt0bLli2xdOlStG7duswDIyIiAnhN+12levOHpaUlbty4UVaxEBER5cPZ\n43LFStoZGRkFlh06dAj6+vplHhQREVEe5my5YiVtBweHQr/pTJgwoUwDIiIiehd72nLFStqLFy/O\nV6arq4vPPvsM1tbWZR4UERER5VespK2rq4tevXopOxYiIiIqQrFeGDJ79mxIpVJlx0JERJSPSFTy\npbIpVtIeMWIEli1bBolEoux4iIiIFIhEohIvlU2xhsePHz+O58+f4/fff4e+vj60tbUV6i9fvqyU\n4IiIiIrXvawaipW0e/Tooew4iIiIClQZe8wlVWTSfvbsGerWrQsfHx9VxUNERESFKHLQoWfPnqqK\ng4iIiD6gyJ62IAiqioOIiKhAHB2XKzJp8zoCERGVN+YiuSKTdk5ODnbs2FFkj1skEmHw4MFlHhgR\nERHAnva7ikza2dnZmDdvXpENMGkTEZFSMWvLFJm0dXV1cfv2bVXFQkREREUo1fu0iYiIlE2kwZ52\nniJv+eLscSIiIvVRZE+7X79+qoqDiIioQLykLVdk0p4/f76q4iAiIioQb/mS4zVtIiJSa8zZcnx3\nChEREYBFixbB2tpa9vmff/7BwIED4ejoiJ49e2Lnzp0K62/fvh1ffPEFHB0dMXDgQISEhMjqpFIp\n5s6di06dOsHZ2Rne3t6Ij48vdYxM2kREpN5EopIvxRQZGYmDBw/KPicmJsLb2xuurq64dOkSFi1a\nhICAAJw/fx4AcPbsWaxYsQLz58/H5cuX4ebmBi8vL7x48QIAEBgYiJs3byIoKAinTp2CsbExJkyY\nUOpTwaRNRERqTaQhKvFSHLm5ufD398eIESNkZYcOHYK5uTkGDx4MPT09ODo6ol+/fti1axcAYOfO\nnejfvz9atmwJXV1duLu7o27dujhy5Aiys7Oxd+9ejBs3DhYWFjAwMICfnx9CQ0MRGRlZqnPBpE1E\nRFXarl27oKenh969e8vKIiIi0KxZM4X1bGxsEBYWJqu3sbEpsD42NhapqakK9SYmJqhTp45s+5Li\nRDQiIlJrypyI9uLFC6xduxZBQUEK5RKJBI0bN1YoMzIyQlJSkqze0NBQoV4sFuPBgweQSCSyz+/X\n521fUuxpExGRelPiNe3Fixfj66+/RqNGjfLVlfYBY8p4QBmTNhERVUmXL19GWFgYvv3223x1xsbG\nsh5znqSkJJiamsrq3+81SyQSmJiYwMTERPa5oPrSYNImIiK1pqyO9qFDh5CQkIAOHTrA2dkZbm5u\nAABnZ2dYWVkhPDxcYf2wsDDY2dkBAGxtbfPVh4aGwt7eHhYWFhCLxQr1CQkJiI+Ph729fanOBZM2\nERGpNWXNHp8+fTpOnDiBgwcP4uDBg9i0aRMA4ODBg+jduzcSExOxfft2ZGZm4urVqzh8+DA8PT0B\nAB4eHjh06BBCQkKQmZmJrVu3Ijk5Gb1794ampibc3d2xfv16PH78GCkpKVi6dClcXFxgaWlZqnPB\niWhERKTWlPUYU7FYrDBZLDs7GwBQp04dAMDGjRuxcOFC/PTTTzAzM4O/vz9atWoFAGjXrh1mzJiB\nqVOnIjExEU2aNMGmTZtk7fn6+iI9PR0DBgyAVCpF27ZtERgYWOqYRUIFfZXXk7//Lu8QiErNqFnj\nD69EVAHom+efyFVWorfuLfG21sO/LsNIyh972kREpN747HEZXtMmIiKqINjTJiIitcZXc8oxaRMR\nkVpj0pZj0iYiIvXGC7kyTNpERKTW2NOW4/cXIiKiCoJJm4iIqILg8DgREak1Do/LMWkTEZF6Y86W\nYdImIiK19qEXf1QlTNpERKTeODwuw4loREREFQR72pVcVnY2dvz9N/4vJAQvkpNhZmIC1/bt0a9D\nBxy/cgVLt28vcDszExPsnDsXAPAkMREb//wTEQ8fIjsnB1b162Ns376wtLCQrX89Kgpbjx7Fw2fP\nUF1PD59bW2NM374wMTRUyXFS1ZKdk4NN/92OI3+fwsukJHxavz58Rw9HW+dWCLkVirGTpxW67Y3T\nxwAAL169wprNW3Ht5i28TEpCfXNzjPJwR8+unVR0FEQfj0m7klu7fz/O3LiBSe7usPzkE1yJiMDq\nffugo62NLp9/Dicbm3zbzNuyBfVq1gQApLx+jcmrV8Oidm0s9vaGpqYmNh86BL+1a7Hlhx9gbGCA\n8AcPMH39erh26AA/Dw+8TE7Gil27MG/LFqycOFHVh0xVwIp1m/Dn0ROY6vstPrdrjj/+Oo5JP87D\ntrWBsGvWFH/vy/9lNHDDL0h88QoAkJubi+9+mIOsrGwsmjUNJsbGOH0+GDMXLkE1PT10bOui6kOi\nInB0XI7D45VYWkYG/rp0CZ49e6KTgwPMa9XCgE6d8Lm1NU5euwZdHR2YGBoqLPfi4nA3NhYje/cG\nAJy+fh0vU1Lw48iRsKpfH5+Zm8Nv8GCkvH6Na3fuAAD2nTmDT+vVw/gBA1DfzAwOVlYY3qsXQmNi\nkPDqVXmeAqqE3mRmYv+Ro3Dv3xeuvXrAwrweJowdCdsmVvjvrn3Q1tZGTRMThSVJkoyTZy9g8rej\nAQAPH8XhTvQ9eA8fAnvbZqhvXg/DBw2EdeNGOPp/Z8r5COl9IpGoxEtlw552Jaavp4e9CxZAT1dX\nodzYwAD3nzzJt35Obi7WHTiAgV27oqZYDAD4sk0btLOzg1hfX7aeUY0aEIlESH79GgAwbcgQZEql\n+fYBAMmvX8PMxKRMj4uqtrgnT5GVlQ2HFrYK5R1aO2Pbnv0FbrN83SZ80bUTmlg2BiDvuWlqaiqs\np62tzV6dOuLscRmV9bTT0tI+uM6mTZtUEEnVIRKJYGRgAD0dHVnZG6kUN+/dQ5MGDfKtf/bGDbxI\nTsZXnTrJyrS1tGQJPM+ViAgIgoCmDRsCAKrp6sLof0k6z+XwcOjr6aGBmVnZHRAR3g5tA/kTrpGR\nGJLkFKT978tkntvhdxByKxQjB38jK2vUsAFa2rfA1l178TzxBQDg9IWLiLobg/69eir5COhjsact\np7KkPXToUEgkkgLrpFIpvv/+e2zcuFFV4VRZq/bsQVp6Ogb95z/56nadOoVerVujRvXqhW7/MjkZ\nK3fvhlPTprBt1KjAdW5ER+OPc+cwuHt36L7zhYGoLFiY14OmhgYi795TKL93/yEAID09Q6F86669\n6NjaGQ0sPlEoD5g7C0KugJ7feMKpex/MWPATZn0/Ec6fOyj3AIhKQWVJu1GjRhg8eDCeP3+uUJ6Q\nkIBBgwYhPDwcu3fvVlU4VY4gCAjcvRunrl3DjKFDYV6rlkJ9aEwM7j95AtcOHQptI+HVK3y3ahWq\n6+lhxtChBa5zPSoKszZtQjs7O7h361amx0AEANWrVUOv/3TB9r1/4FZ4BHJycnD24mWcPHseAKCl\nJb/q9zQ+AecvX8XA/n0U2hAEATMXLkXGmzdY89N8/PfnQIwd6oElq9ch+Mo/Kj0eKgZRKZZKRmVJ\nOyAgAG3atMGgQYMQFxcHAAgNDcWAAQNQs2ZN7Nu3D40bN1ZVOFVKTm4ufgoKwomrVzFn1Ci0t7PL\nt05waCjqm5nlS+Z5niQmYuLKlaimq4vAiRMhrlEj3zqXwsIwc+NGtLezw4/Dh1fKoSlSD34+3nBo\nYYuRE6bAuUdfBO05AO/hntDS1ISBgfx389ylK9CvXg2OLZorbH/hyj+49E8IFs6cirZOLdHUqjFG\nebijU7vW+PnX/6r6cIiKTaUT0WbNmgWxWAwPDw94eHhg3bp1GDFiBCZOnMg/8Eq0eu9eXAwLw5Jx\n42BXyBejy+HhaGNrW2Ddq5QU+P38M8yMjbHI2xv61arlW+d2TAzm/vYb+rRrh/Fubvx5klLV0NfH\n8nk/QpKcAgECjMVi7Nj/JxrWt4D2Oz3tc5euwMnRQaEMeDt7HAAa1lccMreoVw9ngi8p/wDoo/Dv\niZzKZ4/7+vrCyMgIixYtwtSpUzFixAhVh1ClHLl4EcevXCkyYSdKJHiSmAibTz/NV5ebm4s5v/4K\nA319/DRuHKq9NxMdeHud23/zZvR0dobPgAFlfgxE7zt94SJq16wJ26bWsrITZ86hYxv5/dU5OTm4\nFRaBcSPzX8oxq/X2OQSPHj9Bowb1ZeX/xsXB7H/PKCD1wWePy6ksacfExMj+3bp1a4wZMwZ79uxB\nmzZtFGaBcoi87GRkZmLzoUP4wsUF9c3M8ColRaE+72llTxITAQB1TU3ztXH6+nVEPHyI5b6+yMjM\nREZmpqxOR1sbNapVw5a//oK2lhYGd++ebx/6enqcjEZl7q+TpxF1Lwbzpk9B7Zqm2LH/TzyLT8Dg\nAf1k6yQkvoA0Kwvmdevk275jGxfUqV0bc5cFYrL3GJgYG+FyyA2cPn8R3iM8VXkoVBzsacuoLGn3\n7t0bIpEIgiDI/g8A/fr1UyiPjIxUVUiV3t3YWKSmp+NQcDAOBQfnqz+9Zg0AIDU9HQBQXU8v3zrX\no6MhCAImr16dr66HkxOmeXriRnQ0XqakYJC/f751pnp4oKcLny5FZcvf7zv8tGodpvjPR6ZUCofm\ntti0YimMjYxk66SkpgIA9Au4G6JaNT38snIpVm74Bb4zZuNNZibM65hhwtiR8Piqv8qOg4qHw+Ny\nIiEveyrZkwIe5lEQc3Pz4rX399+lCYdILRg148gSVQ765gXfAloWHh89XuJtP6lk992rrKf9bjKO\njY1FUlISAMDExAQW77x4goiISAE72jIqS9rZ2dlYvXo1du/ejZSUFNnwuEgkgqmpKYYMGQIvLy8O\ngxARERVCZUl78eLFuHnzJubNmwcbGxsY/e/ak0Qiwe3bt7FhwwakpaVhypQpqgqJiIgqAM4el1NZ\n0j59+jR27NiBunXrKpQbGBjAwsICdnZ2+Oabb5i0iYhIEUdgZVSWtDMyMmDw3ksl3mVsbIyMjIxC\n64mIqGriZVM5lT3G1N7eHosXL0ZycnK+upcvX2LBggVwdnZWVThEREQVjsp62nPmzMH48ePRpk0b\n1KlTB2KxGIIgQCKRICEhAXZ2dlhdwL3ARERUxfGatozKknadOnWwf/9+hIWF4c6dO7LXdJqYmMDW\n1hZNmzZVVShERFSBcHhcTuXPHm/evDmaN28OqVSKa9eu4fnz53j93kvriYiIKD+VJe0+ffrg8OHD\nAID79+9j7NixSEhIgFgsxqtXr9CkSRNs3LgRtWvXVlVIRERUEbCjLaOyiWiPHj2S/dvf3x8tW7bE\n1atXcfHiRVy8eBH169fH/PnzVRUOERFVECKRqMRLZaOynva7J+/OnTtYv3499PX1Aby9rj1v3jx0\n7txZVeEQERFVOCq/pg0AFhYWyM7Ozleuw1c4EhHR+zh7XEZlw+PZ2dlYu3Ytfv75ZxgYGGDlypWy\nusTERPz4449wcnJSVThERFRBcHhcTmU9bUdHR1y5cgXA2x+ApqamrG7dunV4/Pgx1q1bp6pwiIio\noqiEybekVPY+7fcFBQUhISEB33//PV6/fo0aNWp81PZ8nzZVBnyfNlUWynyfdkLwuRJva9auYxlG\nUv7K5Zr2kydPsGLFCtSuXRstWrRA9+7dyyMMIiKqACrjMHdJqeya9rt+//139OnTB15eXtiyZUt5\nhEBERFThqDxpp6WlYf/+/RgxYgT69OmDuLg4hIWFqToMIiKqKDREJV8qGZUn7X379sHR0RGffvop\ntLW1MWTIEGzdulXVYRARUQXB2eNyKk3aubm5CAoKwujRo2VlgwcPxvnz55GQkKDKUIiIqKIQiUq+\nfMCTJ0/g6+sLFxcXuLi4YOLEibJ8FB0djaFDh6Jly5bo2rUr1qxZg3fnbh8/fhz9+vWDg4MD+vbt\ni7/fmSAtCAJWr16Nbt26oWXLlhg6dCju3btX6lOh0qR94sQJmJiYoGXLlrIyQ0ND9OvXD9u2bVNl\nKEREVEGINEQlXj7E29sburq6OHXqFP766y9IJBLMnj0bb968gZeXFxwcHHDu3Dls2LAB+/fvx65d\nuwAAUVFR8PPzg6+vL65cuYKJEydiypQpuHv3LgBgx44dOHDgANauXYvz58/D0dERXl5eyMzMLNW5\nUGnSbtKkicJDVfL4+vriiy++UGUoRERUxaWkpMDW1hZ+fn6oUaMGTE1NMXDgQFy7dg1nz55FRkYG\nfH19oa+vD0tLS3h6esqS9p49e9C2bVt069YNurq66Nq1K1q3bo29e/cCAHbu3Ilhw4bB2toa1atX\nx/jx45GamooLFy6UKmaVJu1PP/0U5ubm+crFYjFsbW1VGQoREVVxhoaGWLx4MczMzGRlz549g5mZ\nGSIiImBlZQUtLfmd0TY2Nrh79y4yMzMRERGBZs2aKbRnY2ODsLAwvHnzBjExMbCxsZHVaWtrw8rK\nqtQTr8vlli8iIqJiU+I17Xc9ePAA69evx7hx4yCRSGBoaKhQb2RkhNzcXCQnJxdYLxaLkZSUhOTk\nZAiCALFYXGB9aTBpE7OaJVkAABGlSURBVBGRWlPF7PGwsDAMGTJEdjsyAHzogaGlrS8JJm0iIlJv\nSu5pX7hwAcOHD4ePjw98fHwAvH1ltEQiUVhPIpFAU1MTRkZGMDY2LrDe1NQURkZG0NDQKLDexMSk\nFCeCSZuIiNScMmeP3759G5MmTcKSJUswePBgWbmtrS2io6MhlUplZaGhoWjatCl0dHRga2uL8PBw\nhbbCwsJgZ2cHXV1dWFpaKly/lkqliIqKgr29fanOBZM2ERFVSdnZ2Zg5cyZ8fX3RrVs3hbqOHTvC\nyMgIa9asQXp6OqKiohAUFARPT08AgLu7O65evYqTJ09CKpXi2LFjCAkJgbu7OwDAw8MDQUFBuHv3\nLtLT0xEYGIjatWujbdu2pYq53N7yVVp8yxdVBnzLF1UWynzL16tb/5R4WxN7p0LrQkJC4OHhAR0d\nnXx1x48fx5s3b+Dv74/Q0FCIxWIMGzZM4eFgp06dwvLlyxEXF4eGDRti6tSp6NChg6x+7dq12Llz\nJ1JSUuDo6Ii5c+eiQYMGJT4WgEmbqFwxaVNlodSkfftaibc1sWtVhpGUv3J5NScREVGxVcJniJcU\nkzYREam1yvjij5Ji0iYiIvVWCV+xWVKcPU5ERFRBsKdNRERqTSRi/zIPzwQREVEFwZ42ERGpN05E\nk2HSJiIitcbZ43JM2kREpN44e1yG17SJiIgqCPa0iYhIrXF4XI5Jm4iI1BuTtgyHx4mIiCoI9rSJ\niEi98eEqMkzaRESk1kScPS7Dry9EREQVBHvaRESk3jgRTYZJm4iI1Bpv+ZJj0iYiIvXGiWgyPBNE\nREQVBHvaRESk1jh7XI49bSIiogqCPW0iIlJvnIj2/+3dfVCN+f/H8WelI9VqVKhVRBPKWBUjIosR\nTqxW1hiL2dZmy82KbCM2jXIzzbjJXW6Wat0UGay7LGpXmGaNZaOsLNaaQntETqnolM7vD+Nwvkn9\ntkWH92Pm/HGu63Nd1+d9XNPL9Tmf+uhIaAshhGjSZPb4cxLaQgghmjaZPa4joS2EEKJpk4loOvLf\nFyGEEMJASGgLIYQQBkKGx4UQQjRpMhHtOQltIYQQTZtMRNOR0BZCCNGkyZP2cxLaQgghmjZ50taR\nT0IIIYQwEBLaQgghhIGQ4XEhhBBNmqzy9ZyEthBCiKZNJqLpSGgLIYRo0oxkIpqOhLYQQoimTZ60\ndYy0Wq32bXdCCCGEEPWTMQchhBDCQEhoCyGEEAZCQlsIIYQwEBLaQgghhIGQ0BZCCCEMhIS2EEII\nYSAktIUQQggDIaEt9ERERODq6kr37t11Lw8PD93+0tJS5syZQ//+/fH29mbOnDk8fPhQt79Lly6c\nOHFC75wrV65k0KBBFBYWvrE6xPtl0qRJuLm56d23I0aM0O0vLCwkJCQELy8vPv74Y2JiYtBoNADc\nunWLLl26cPXqVV17rVbLt99+y6effkppaekbr0eIukhovycuXbrEzz//3KC2/v7+5Obm6l7Z2dm6\nfZGRkajVavbv38+hQ4dQq9VERUXVea7ExET27t1LUlIS9vb2ja5DvJ9u3LjBkSNHePLkSZ1tpk6d\nqnffpqWl6fbNmDGDVq1akZ6eTkpKCtnZ2axZs6bOcy1ZsoRLly6RmJhIy5Yt/9NahGgMCe13WE1N\nDRkZGUycOJGQkBBKS0v1nkRefEVGRtZ7vnv37pGenk5YWBi2trbY2Ngwa9Ysjh07RnFxca32e/fu\nZdOmTSQkJODk5PQaKhTvC4VCQWJiIr6+viQlJVFWVtbgY3Nzc7l8+TLh4eG0bNmSdu3aERwczO7d\nu6mpqanVfu3atfzyyy/88MMPWFtb/5dlCNFo8rfH30EVFRX8+OOPbNu2jWbNmhEYGIi/vz8KhYLR\no0fXe/yff/7JuHHjuHbtGu3btycqKgpPT0/y8vIwMjKia9euurZdu3ZFq9WSl5dHv379dNszMjKI\njY1ly5Yteu2F+DccHBzYs2cPZ8+eJTExkfj4eMaMGcOkSZNwcHAA4MyZM6Snp1NQUICbmxsxMTE4\nOzvzxx9/YG9vrxfA3bp1o6SkhPz8fJo1e/5jcPv27aSmppKcnIydnd0br1OI+siT9jvm6tWrDBo0\niGPHjjF//nwOHz7M2LFjUSgUDTre0dERJycnVqxYwenTp/Hx8SEoKIj79++jVquxsLDAxMRE197U\n1BQLCwsePHig23bmzBlmz57NsGHD6NGjx39eo3h/9e7dm40bN5KamkpFRQWffPIJ27Ztw9nZGWdn\nZ5KSksjMzKRdu3ZMmTKFyspK1Gp1rSFuKysrAL379tChQyxZsoQJEybQoUOHN1qXEA0lof2OKSsr\nQ6PR4OHhgZubG0b/z9Vxpk+fTlxcHA4ODlhYWDBr1izMzc1JT08Hnk7QqU9aWhoREREcPHiQ48eP\n/6s6hHgVR0dH3N3dad26Nf/88w8LFy4kJiYGGxsbrKysiIqKQqVScfbsWaBh9+3x48cJDw9nw4YN\nXLhw4XWXIMS/IsPj7xhPT0+Sk5NJSkpi6NChDB8+nMmTJ+Pi4sLt27cZPnz4S4/z9/dn8eLFtbab\nmJhgb2/P3bt36dmzJ+Xl5VRVVWFqagpAVVUV5eXl2NjY6I5ZuHAhQ4YMQaFQMHfuXNq3by9D5OI/\nUVJSws6dO9mxYwcODg6EhYXh6+tbq52lpSVWVlbcvXsXa2tr1Gq13v5n71+8b1etWoWrqyulpaXM\nmDGDPXv2yBC5aHIktN9Bbm5uLFu2DJVKRXJyMhMnTuSjjz5i5syZ5Obm1nmcVqslNjaW0aNH60JW\no9GQn5+Po6Mjrq6uGBkZcfnyZd2w96VLlzAxMcHNzU13nmfD52PHjiU3N5dp06axZ88emdQj/jW1\nWs26devYv38/Pj4+xMfH6+7BsrIyli9fztSpU2nbti0AxcXFFBcX4+joiKWlJSqViqKiIlq3bg1A\nTk4ONjY2ODo6cvv2beD5fRsaGkpeXh7Tpk0jJSUFMzOzt1CxEC8nw+PvsLZt2xIWFkZmZiaDBw/m\n4sWLr2xvZGTErVu3iI6ORqVSUV5ezvLlyzE1NWXo0KFYW1ujVCpZtWoV9+/fp6ioiJUrVzJq1Cjd\nd4T/KzIykjZt2vDNN99QVVX1OsoU74GCggJMTU05ePAgcXFxenMlLC0tuXjxIosXL0atVlNSUkJ0\ndDSdO3emV69euLm54e7uzrJly3j48CEFBQVs2LCBCRMmvPTrI2NjY5YvX05ZWRnz589/k2UKUS8J\n7fdAixYtGD9+PBMnTqy37ZIlS3ByciIgIABvb2/y8vLYunUrFhYWAERHR2Nra8vQoUNRKpU4ODiw\nYMGCOs+nUChYs2YN+fn5xMTE/Gc1ifdL9+7dmTt3Lh9++OFL98fHx6PVahk2bBgDBw6kqqqKzZs3\nY2z89Efc6tWrKS0txcfHh7FjxzJgwABCQkLqvF7Lli2Jj4/nxIkTbNy48bXUJMS/YaRtyAwNIYQQ\nQrx18qQthBBCGAgJbSGEEMJASGgLIYQQBkJCWwghhDAQEtpCCCGEgZDQFkIIIQyEhLYQL9GlSxd2\n7NgBwPr16xkwYMAbvf7atWvx8vJ6rdeIiIggICDgrZ9DCNFwEtqiyZs0aRKurq56638/++MYV65c\nee3XnzZtGqdOnWpw+x07dnD//v3X2KM3E+pCiKZHQlsYBF9fX3Jzc3Wv3bt3Y2ZmxldffaW3vOLb\nVlpaytKlS197aAsh3k8S2sIg2dnZERUVxb179zhz5gzw9Ik8KiqKkJAQ3N3dUalUAKSmpjJq1Cg8\nPDzo168f0dHRVFRU6M6VnZ1NQEAA7u7uKJVKTp48qXet/32qLS4uJiIiAi8vL3r37k1ISAg3b97k\nypUreHt78+TJEwICApgzZw4AhYWFzJw5k/79+9OjRw8+++wzsrKydOfTaDQsXryY/v3706tXL+bO\nncujR48a/RllZWUxbtw43N3d6dWrF1988cVLRyaSk5MZOHAgnp6eTJ48mcLCQt2++vr+snMNHz4c\nd3d3vLy8CA0N5d69e42uRQjxlIS2MFjV1dUAumVC4emayEqlkvPnz9OmTRv27dvHsmXLmDdvHufP\nn2f79u2cO3eOyMhIACoqKggODsbV1ZWsrCy2bt3Krl27XnndmTNnUlRUxE8//URmZiaWlpYEBQXh\n4uJCQkICAPv27WPFihVoNBoCAwNp3rw5hw4d4uzZs4wcOZLg4GCuXr0KQFJSEvv372fdunX8+uuv\nDBw4kNTU1EZ9Nvfv3yc4OBgfHx/OnTvHyZMnsbKyYvr06Xrtbt68ybVr1zh8+DDHjx+ntLSUmTNn\nAjSo7y+6cOECMTExzJs3j+zsbI4ePUpVVRWxsbGNqkUI8ZyEtjA4Wq2WO3fusGjRImxtbfWegm1s\nbPD398fExAQjIyO2bdvGmDFj6Nu3L8bGxnTq1Inp06dz9OhRHj9+zKlTpygpKWHWrFlYWFjoViSr\ny5UrV/jtt98IDQ3F2toac3NzIiIiCAsL4/Hjx7Xanzp1ivz8fBYsWECrVq1o3rw5gYGBODk5kZaW\nBsChQ4fw8/PD3d0dU1NTlEolvXv3btRnZGNjQ1ZWFsHBwTRr1gwLCwtGjBjBrVu3KCoq0rWrqakh\nPDwcS0tLbG1tmTx5Mjk5OahUqgb1/UWlpaUAmJubY2RkRKtWrYiPj2f58uWNqkUI8Zyspy0MQnp6\nOt27d9e9t7W1xdPTk127dvHBBx/otjs6Ouodd+PGDa5du0ZKSkqtc6pUKgoLCzEzM9Otswzg4uJS\nZz9u3rwJgIODg15f/Pz8Xtr+xo0b1NTU0K9fP73tWq1WNwx9584d/P399fZ37tyZ33//vc5+NMSR\nI0fYuXMnBQUFVFdX82xtoMrKSl0bR0dH3QpuAE5OTro+NaTvL+rTpw9+fn5MmjSJrl270qdPH5RK\npd4ymkKIxpHQFgbB19eXNWvW1NtOoVDovX82WS04OPil7SsrK3XLNz7zqoXvTExM6m3zv9dXKBTk\n5ubW2Uaj0dTqQ01NTYPOX5cDBw4QHR3NokWLGDFiBObm5mRkZNQaHn/ZetIAzZs3b1DfX6RQKIiL\niyMsLIzTp0+TmZnJuHHjCA4OZvbs2Y2qRwjxlAyPi3dax44duXz5st62kpIS1Go18HRCW0VFBcXF\nxbr9r/o1smdPon/99ZduW3FxMQkJCS+dMd6xY0c0Gg3Xr1/X215QUKALfjs7O27fvq23v7G/ynb+\n/Hk6dOjA2LFjMTc3B+DixYu12hUUFOgN6z8bSbCzs2tQ319UXV2NWq3G0dGRzz//nO+//56QkBC2\nb9/eqFqEEM9JaIt3WmBgIBkZGRw4cACNRoNKpSIsLEw3s9vHxwczMzNWr15NRUUFKpWKtWvX1nry\nfcbFxQUvLy/i4uJQqVQ8evSIVatWkZKSQsuWLWnRogXwNNTLysro168fnTt3Jjo6mjt37lBdXc2R\nI0fw8/PTDX/7+vqSlpZGbm4uGo2Gw4cPc+HChUbV3aFDB+7evcvff/9NeXk5e/fuJScnB6DW0HZc\nXBzl5eWoVCq2bNmCt7c31tbWDer7izZt2kRAQABXrlxBq9VSUlLC9evX6dSpU6NqEUI8J8Pj4p2m\nVCopLi5m/fr1fPfdd1hYWDBkyBDCw8OBpxO2Nm7cSGxsLH379sXe3p6IiIhXfp8cHx9PdHQ0fn5+\nGBsb4+HhwZYtWzA1NcXV1RVvb2/Cw8Px8vIiISGBDRs2EBsby6hRo6isrMTZ2ZmVK1fSs2dPAEJD\nQykrK+Prr79Go9EwePBgvvzyS7Zu3frK2tRqtd73/M9s3ryZ8ePHk5OTw5gxY1AoFIwcOZL4+HiC\ngoIICgoiPj4egG7dumFvb49SqeThw4d4enqydOlSAIyNjevt+4umTJlCWVkZwcHBPHjwAEtLS3r2\n7ElcXFzD/rGEEPUy0jb0yzkhhBBCvFUyPC6EEEIYCAltIYQQwkBIaAshhBAGQkJbCCGEMBAS2kII\nIYSBkNAWQgghDISEthBCCGEgJLSFEEIIAyGhLYQQQhiI/wP+9e3kcnmEcQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb414ea8750>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "UJuwXtFKS-vl",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "39798abe-ba2b-4b85-87e7-5f2a77333d20",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271638030,
          "user_tz": -60,
          "elapsed": 503,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import accuracy_score\n",
        "\n",
        "accuracy = accuracy_score(adult_test_new[dep_var], predictions)\n",
        "\n",
        "print 'The error rate is ', 1- accuracy"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The error rate is  0.20776892430278882\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "gB_9Q_gwTFYk",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "> I chose the most basic classification algorithm namely logistic regression model, this is mainly due to its simplicity. This model classifies nearly 80% of the labels correctly. Therefore, in order to increase the accuracy of this model I would consider another model in the following section.\n",
        "\n",
        "#### Logistic regression model with LASSO-type penalisation (L1)"
      ]
    },
    {
      "metadata": {
        "id": "EvVQou3_TB-s",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 404
        },
        "outputId": "8e5bbc97-d453-4c1b-eea2-ff64a0ffc637",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271685903,
          "user_tz": -60,
          "elapsed": 921,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "model = LogisticRegression(fit_intercept = True, penalty='l1', C = 1).fit( adult_train_new[ind_var],adult_train_new[dep_var])\n",
        "\n",
        "# predictions on the test set \n",
        "\n",
        "predictions = model.predict(adult_test_new[ind_var])\n",
        "\n",
        "plot_confusion_matrix(adult_test_new[dep_var], predictions)\n",
        "\n",
        "accuracy = accuracy_score(adult_test_new[dep_var], predictions)\n",
        "\n",
        "print 'The error rate is ', 1- accuracy"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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F9diB/ahbpzYGDR2Jp8/k1xiXrlyNpStXAwAirnBUqCLQ0tLC999/j2HDhmHH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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb414ea81d0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "The error rate is  0.15172642762284194\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "N2lJ4M_ITRSq",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Logistic regression with LASSO type penalisation does better than non-regularized logistic regression. The error rate has gone down by almost 5% by including a L1 type regularization. The reason why I considered this model is as follows:\n",
        "1. L1 type of regularization is known for its automatic feature selection therefore it tends to discard less important feature. \n",
        "\n",
        "2. I did consider L2 type penalization but it does not do better than L1 type penalization. \n",
        "\n",
        "\n",
        "#### Ensemble of Decision Trees Classifier (Extreme Gradient Boosting Classifier)"
      ]
    },
    {
      "metadata": {
        "id": "tPD67xcaTNkJ",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "outputId": "5e814fec-6209-4c6e-aacc-baf6ce1205b9",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530271808372,
          "user_tz": -60,
          "elapsed": 90363,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "from xgboost import XGBClassifier\n",
        "\n",
        "\n",
        "# Inititate the algorithm and set the parameters, these are based on my own experience \n",
        "\n",
        "xgb_params0={'colsample_bytree': 0.87, 'silent': 1, 'nthread': 8, 'min_child_weight': 10,\\\n",
        "    'n_estimators': 1000, 'subsample': 1, 'learning_rate': 0.01, 'objective': 'reg:logistic',\\\n",
        "    'seed': 10, 'max_depth': 7, 'gamma': 0.0, 'eval_metric' : 'error'}\n",
        "\n",
        "model = XGBClassifier(**xgb_params0)\n",
        "\n",
        "model.fit(adult_train_new[ind_var],adult_train_new[dep_var])\n",
        "\n",
        "predictions = model.predict(adult_test_new[ind_var])\n",
        "\n",
        "plot_confusion_matrix(adult_test_new[dep_var], predictions)\n",
        "\n",
        "accuracy = accuracy_score(adult_test_new[dep_var], predictions)\n",
        "\n",
        "print 'The error rate is ', 1- accuracy"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python2.7/dist-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
            "  if diff:\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fvn3o3r27omft7u6O3bt345dffkHfvn1x6NAhLFy4UDH52tvbG82bN0dISAjq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\nIuIm/h+59jkSpoSaaQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7fb414cea110>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "The error rate is  0.1294820717131474\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "zKWTqZi8TZUy",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "> Extreme gradient boosting gives the minimal error rate so far which is roughly 13% resulting into 87% of accuracy on the test set. Finally, we cross-validate our final model to check if there is any overfitting.\n",
        "\n",
        "#### Cross-validation of the tree based model using 5-fold "
      ]
    },
    {
      "metadata": {
        "id": "Eld_7JRNTVoI",
        "colab_type": "code",
        "colab": {
          "autoexec": {
            "startup": false,
            "wait_interval": 0
          },
          "base_uri": "https://localhost:8080/",
          "height": 224
        },
        "outputId": "d4f0f891-84b4-49aa-bbec-87dae2d0bbe2",
        "executionInfo": {
          "status": "ok",
          "timestamp": 1530272175778,
          "user_tz": -60,
          "elapsed": 367365,
          "user": {
            "displayName": "Divakar Kumar",
            "photoUrl": "//lh3.googleusercontent.com/-LtRQzmxVRvY/AAAAAAAAAAI/AAAAAAAAAFU/r_yXitppHYI/s50-c-k-no/photo.jpg",
            "userId": "111511324323120384224"
          }
        }
      },
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import cross_val_score\n",
        "from xgboost import XGBClassifier\n",
        "\n",
        "from sklearn.pipeline import make_pipeline\n",
        "\n",
        "# we make a pipeline of the above three classifiers\n",
        "clf = make_pipeline(XGBClassifier(**xgb_params0))\n",
        "\n",
        "scores = cross_val_score(clf, adult_train_new[ind_var],adult_train_new[dep_var], cv=5)\n",
        "\n",
        "print(\"Average Error Rate: %.2f%% (+/- %.2f%%)\" % ((1-scores).mean()*100, (1-scores).std()*100))"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python2.7/dist-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
            "  if diff:\n",
            "/usr/local/lib/python2.7/dist-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
            "  if diff:\n",
            "/usr/local/lib/python2.7/dist-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
            "  if diff:\n",
            "/usr/local/lib/python2.7/dist-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
            "  if diff:\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Average Error Rate: 13.21% (+/- 0.30%)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python2.7/dist-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
            "  if diff:\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "metadata": {
        "id": "yZM1tjYWTkp3",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "### Conclusion based on the 5-fold cross-validation\n",
        "\n",
        "> Based on our empirical study on error rate of the Logistic regression model and the Penalised logistic Regression model it is evident that our tree based model is the best among all. Upon using 5-fold cross-validation for the decision tree based model, the average error rate is roughly 13% which beats both versions of the logistic regression model. I did not think it is useful to cross-validate earlier two versions of the logistic regression model since the average error rate in the cross-validated extreme gradient boosting model is roughly 13% with a standard deviation of 0.3%. Therefore none of the above two models can beat the accuracy of the extreme gradient model."
      ]
    }
  ]
}