Skip to content

Files

Latest commit

3fb40c4 · Jan 7, 2025

History

History

Classification

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025
Jan 7, 2025

Trees and Ensemble Classification Projects

This repository contains mini-projects that apply decision trees and ensemble learning models to various datasets. Each project demonstrates the application of classification techniques to solve real-world problems, showcasing the effectiveness of these models in diverse contexts.


Projects

1. Basic Classification with Synthetic Data

This project implements a decision tree classifier on a synthetic dataset generated using scikit-learn's make_classification function. The dataset consists of two classes and four features, allowing users to learn the basics of training, optimizing, and visualizing decision tree models.

  • Dataset Source: Synthetic dataset generated using scikit-learn.

2. Cirrhosis Patient Survival Prediction

This project predicts the survival status of cirrhosis patients based on clinical and demographic data. Various machine learning models, including ensemble techniques, are used to classify patient status into categories: death, censored, and censored due to liver transplantation.


Requirements

  • pandas
  • numpy
  • scikit-learn
  • matplotlib
  • seaborn

Feel free to explore each project to understand the methodologies and results in more detail!