XGBoost vs CatBoost vs LightGBM vs Adaboost vs GBM

In this video we will compare the speed and performance of 5 different boosting classifiers in Python. We will make use of the Breast Cancer dataset available from the UC Irvine Machine Learning Repository. Citation: Zwitter, Matjaz and Soklic, Milan. (1988). Breast Cancer. UCI Machine Learning Repository. https://doi.org/10.24432/C51P4M. The break-down of the video is as follows: Introduction 00:00 Model descriptions 00:43 Start coding 2:29 Preprocessing data 3:07 XGBoost 10:15 CatBoost 12:08 LightGBM 12:47 Adaboost 13:54 GBM 14:34 Conclusions 15:00 The best way to keep up-to-date with my video/blog content is to sign up for my monthly Newsletter! Please visit: https://insidelearningmachines.com/newsletter/ to register. The notebook presented here can be found at: https://github.com/insidelearningmachines/Blog/blob/main/%5BVideo%5D%20xgboost%20vs%20lightgbm%20vs%20catboost%20vs%20adaboost%20vs%20gbm.ipynb The dataset used here can be found at: https://archive.ics.uci.edu/dataset/14/breast+cancer My blog article on Adaboost classifiers can be found here: https://insidelearningmachines.com/adaboost_classification_algorithm/ The homepage of my blog is: https://insidelearningmachines.com Other social media includes: Twitter: https://twitter.com/inside_machines Facebook: https://www.facebook.com/Inside-Learning-Machines-112215488183517 #machinelearning #datascience #boosting #xgboost #insidelearningmachines