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heirarchical-clustering

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In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).

  • Updated Jul 6, 2023
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A Repository Maintaining My Summer Internship Work At Datalogy As A Data Science Intern Working On Customer Segmentation Models Using Heirarchical Clustering, K-Means Clustering And Identifying Loyal Customers Based On Creation Of Recency, Frequence, Monetary (RFM) Matrix.

  • Updated Jan 10, 2021
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A hub that contains notebooks that implement Regression models, illustrates LR via Gradient Descent, compares K-means vs Spectral vs Hierarchical, compares PCA vs t-SNE

  • Updated Aug 28, 2021
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Unlock personalized content recommendations on Netflix with my cutting-edge ML project. Say goodbye to aimless scrolling and elevate your binge-watching experience with our user-centric content-based recommender system.

  • Updated Apr 27, 2024
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This repository contains all the projects carried out to understand and experiment on Machine Learning using Python. Projects scripts are created to build model on classification , clustering and regression machine learning models for future predictions.

  • Updated Apr 12, 2022
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Problem Statement Perform clustering (Hierarchical,K means clustering and DBSCAN) for the airlines data to obtain optimum number of clusters. Content This data set contains statistics, in arrests per 100,000 residents for assault, murder, and rape in each of the 50 US states in 1973. Also given is the percent of the population living in urban areas

  • Updated Apr 20, 2024
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Performed clustering analysis on OnSports player data for the English Premier League. The clustering analysis successfully identified 4 unique player clusters and uncovered valuable business recommendations by identifying trends and patterns in the EDA, meeting the objective of determining player pricing next season.

  • Updated Jan 6, 2023
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