Decision Trees and Ensembling techniques in R studio. Bagging, Random Forest, GBM, AdaBoost & XGBoost in R programming
- Students will need to install R Studio software but we have a separate lecture to help you install the same
What you’ll learn:
- Solid understanding of decision trees, Bagging, Random Forest and Boosting techniques in R studio
- Understand the business scenarios where decision tree models are applicable
- Tune decision tree model’s hyperparameters and evaluate its performance.
- Use decision trees to make predictions
- Use R programming language to manipulate data and make statistical computations.
- Implementation of Gradient Boosting, AdaBoost and XGBoost in R programming language
Created by Start-Tech Academy
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