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Decision Trees and Ensembling techinques in R studio. Bagging, Random Forest, GBM, AdaBoost and XGBoost in R programming
Rating: 4.4 out of 54.4
(78 ratings)
33,102 students
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Last updated 10/2020
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15 downloadable resources


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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
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Decision Trees and Ensembling techinques in R studio. Bagging, Random Forest, GBM, AdaBoost and XGBoost in R programming
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6 hours on-demand video
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15 downloadable resources

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Decision Trees and Ensembling techinques in R studio. Bagging, Random Forest, GBM, AdaBoost and XGBoost in R programming
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