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Exercise

The Random Forest model

Comparing the performance of multiple Machine Learning models on the same dataset is an important step towards deciding which one meets your business goals more closely.

In this series of exercises, you are going to see both Random Forests (RFs) and Gradient Boosted Trees (GBTs) in action! You will be predicting the rating of a Google Play app based on its category, number of user reviews, size (in megabytes) of the app file, number of installs and content type.

A simplified version of the Google Play apps dataset has been already split into 75% training and 25% testing for you. Will RFs beat GBTs on this dataset? You will find out soon enough!

Instructions 1/4
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  • Load the randomForest package, then fit a Random Forest model with 500 trees to the training dataset to predict Rating using all other variables. Name this model mdlRF.
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