#12 What is Bagging, Random Forest & Extreme Gradient Boosting | Ensemble Methods with R

Week-12:
Includes Random forest regression, Random forest classification, extreme gradient boosting regression and extreme gradient boosting classification examples.

R File and CTG data: https://github.com/bkrai/Statistical-...

TIMESTAMPS
00:00 Introduction
01:27 Supervised Vs Unsupervised Learning
06:25 Model development and deployment
10:17 High variability in regression trees
13:22 Ensemble methods
14:32 Weather forecast example
16:21 What is Bootstrap aggregating (bagging)?
20:34 Regression tree comparison with Boston housing data
21:51 Bagging variable importance
23:22 Regression tree performance - root mean square error (RMSE) and R-square
25:58 What is random forest? Why it is called random forest? How it differs from bagging?
30:41 Random forest parameter mtry
33:06 Random forest variable importance for regression problem
33:40 Random forest regression: Tree Vs Bagging Vs Random Forest Visualization
35:22 Regression performance: RMSE & R-sq for tree Vs bagging Vs RF
44:22 Explaining individual predictions
48:35 What is extreme gradient boosting?
54:57 Extreme gradient boosting parameters
57:56 Extreme gradient boosting variable importance
58:30 Regression performance: Tree Vs Bagging Vs Random Forest Vs XGB
59:07 Classification tree with CTG data
01:00:13 Bagging variable importance
01:00:34 Bagging - confusion matrix
01:02:01 Random forest classification example
01:08:15 Random forest classification - parameters
01:08:51 Random forest variable importance
01:13:09 Tree Vs Bagging Vs RF
01:14:23 Classification - Extreme gradient boosting variable importance
01:15:22 Extreme gradient boosting confusion matrix
01:16:08 Regression trees with R - Bagging, RF & XGB
01:33:49 Classification trees with R - Bagging, RF & XGB

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.

#XGB #ExtremeGradientBoosting #ExtremeGradientBoostingClassification #ExtremeGradientBoostingRegression #RandomForest #RandomForestAlgorithm #RandomForestClassification #RandomForestRegression #MachineLearning #RProgramming