What you’ll learn
- The algorithm behind recursive partitioning decision trees
- Construct conditional inference decision trees with R`s ctree function
- Construct recursive partitioning decision trees with R`s rpart function
- Learn to estimate Gini´s impurity
- Construct ROC and estimate AUC
- Random Forests with R´s randomForest package
- Gradient Boosting with R´s XGBoost package
- Gradient Boosting parameter tuning
- Deal with missing data
Who this course is for:
- The ideal students of this course are university students and professionals interested in machine learning and business intelligence.
How to Enroll Decision Trees, Random Forests & Gradient Boosting in R course?
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