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.
Видео eXtreme Gradient Boosting XGBoost Algorithm with R - Example in Easy Steps with One-Hot Encoding канала Dr. Bharatendra Rai
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.
Видео eXtreme Gradient Boosting XGBoost Algorithm with R - Example in Easy Steps with One-Hot Encoding канала Dr. Bharatendra Rai
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