eXtreme Gradient Boosting XGBoost Algorithm with R - Example in Easy Steps with One-Hot Encoding

Provides easy to apply example of eXtreme Gradient Boosting XGBoost Algorithm with R . Data file and R code: https://github.com/bkrai/Top-10-Machine-Learning-Methods-With-R Machine Learning videos: https://goo.gl/WHHqWP Timestamps: 00:00 eXtreme Gradient Boosting XGBoost with R 00:04 Why eXtreme Gradient Boosting 00:34 Packages and Data 02:02 Partition Data 03:25 Create Matrix & One Hot Encoding 07:35 Parameters 09:59 eXtreme Gradient Boosting Model 11:51 Error Plot 16:50 Feature Importance 18:00 Prediction and Confusion Matrix - Test Data 24:03 More XGBoost Parameters Includes, - Packages needed and data - Partition data - Creating matrix and One-Hot Encoding for Factor variables - Parameters - eXtreme Gradient Boosting Model - Training & test error plot - Feature importance plot - Prediction & confusion matrix for test data - Booster parameters R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.