Machine learning Classification for Family Determination to various Generations with their Ages, Hight, Weight, etc...

Run histogram-based gradient boosted trees binary classifier on generated data and interpret results with standard metrics, SHAP, and supervised clustering

This repository contains Python scripts to train and deploy a Gradient Boosting Machine (GBM) classifier for predicting employee efficiency based on various features such as age, experience, education level, and average handling time. The model is implemented using scikit-learn and pandas libraries.

Simple and flexible classical ML module that can be used for recording baseline ML performance.

Ce projet est une proposition de solution au Rakuten Data Challenge. L'objectif est de mettre en œuvre différentes méthodes de Machine Learning et Deep Learning pour résoudre le problème.

This project implements machine learning models to predict the status of water pumps in Tanzania using data from DrivenData's competition. The project includes preprocessing steps, model evaluation using cross-validation, and hyperparameter optimization with Optuna.

Scripts, figures and working notes for the participation in FungiCLEF-2022, part of the 13th CLEF Conference, 2022

A curated list of gradient boosting research papers with implementations.

Predicting Annual Income from Census Data: A Binary Classification Analysis using various ML Techniques

This project applies Gradient Boosting to predict the outcome of Kickstarter campaigns and uses K-means Clustering to uncover project trends, providing deeper insights into their distinct features.

Comparative Analysis of Decision Tree Algorithms in Number Classification: Bagging vs. Random Forest vs. Gradient Boosting Decision Tree Classifiers

Predicting the success or failure of Kickstarter projects using a gradient boosted random forest classifier.

FederBoost's Federated Gradient Boosting Decision Tree Algorithm, Federated enabled Membership Inference

This repository contains 2 ML projects for my internship under NeuroNexus Innovations.

Titanic Dataset Survival Prediction by using Machine Learning Classifiers

42 school project. Process EEG datas by cleaning, extracting, creating a ML pipeline implementing a dimensionality reduction algorithm before finding the right classifier and handling a real time data-stream with sklearn.

Kaggle Gold Medal Solution. ICR - Identifying Age-Related Conditions.

A digits classification model using Gradient Boosting Classifier, with CI using GitHub Actions.

flask app for credit scoring with gradient boosting classifier machine learning algorithm

This repository provides examples of image feature vector classification using PySpark and scikit-learn, offering flexibility in choosing between the two popular machine learning libraries.