Fast boosting with AdaBoost and Bandit
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Updated
Sep 19, 2019 - Jupyter Notebook
Fast boosting with AdaBoost and Bandit
Supervised learning and unsupervised in R, with a focus on regression and classification methods.
TP2 de Aprendizado de Máquina (2021/1) no DCC/UFMG.
This repository consists of projects on Big Data and Data Analytics as a part of our curriculum for PGDM- BDA (4th Term) at FORE School of Management, New Delhi.
Predicting the physical form of polymer samples based on laboratory measurements of the particle and bulk densities of the samples.
A curated list of gradient boosting research papers with implementations.
A machine learning project predicting school dropouts in El Salvador.
An R package that makes xgboost models fully interpretable
Machine Learning Techniques
ML Algorithms notebook with dataset. Will keep on Updating this Repo.
Part of Machine Learning coursework
Pagina de servicio de Boosting en League Of Legends
XGBoost. LightGBM. CatBoost.
This project explores interpretable machine learning models using Decision Trees for classification and LASSO, Ridge Regression, PCR, and Boosting techniques for regression, applied to Acute Inflammations and Communities and Crime datasets, focusing on model interpretability, feature analysis, and optimization.
Implementing random forest models in R with bagging and boosting.
This is Kaggle challenge for house prediction, it has alot of missing values which needs to be cleaned. i have used Regression ,Boosting, and Deep Neural network and tuning them.
Algorithms from scratch to know how the algorithms work.
Using Logistics, Classification, and KNN modelling to predict if a credit card account will default.
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