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decision-tree-regressor

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Exploring the impact of socioeconomic indicators on hardship in Chicago neighborhoods using machine learning. Leveraging Linear Regression, Decision Tree, random forest, and Agglomerative Clustering, the project identifies key factors—unemployment, lack of a high school diploma, and poverty—highlighting disparities in the dataset from 2008-2012

  • Updated Dec 16, 2023
  • Jupyter Notebook

Data in the social networking services is increasing day by day. So, there is heavy requirement to study the highly dynamic behavior of the users towards these services. The task here is to estimate the comment count that a post is expected to receive in next few(H) hours. Data has been scraped from one of the most popular social networking site…

  • Updated Aug 8, 2022
  • Jupyter Notebook

The overall objective of this project is to critically analyze and develop the relationships of quantitative factors affecting life expectancy in 193 countries between 2000 and 2015 that underlie changes in life expectancy. The importance of predicting life expectancy arises because of its important role as an indicator of the overall health.

  • Updated Sep 15, 2023
  • Jupyter Notebook

This repository contains implementations of popular machine learning algorithms including Support Vector Machine (SVM), Decision Tree, and Naive Bayes. Each algorithm is implemented separately, providing clear and concise examples of their usage for classification tasks.

  • Updated Mar 9, 2024
  • Jupyter Notebook

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