Task $9-$ Feature Importance, part $2(10$ Points$).$

The value of Feature Importance

This follow$-$on task will use the same RandomForestClassifier model as in your get$\_$top$\_$features$()$ function.

The new model will use a portion of the output returned by the get$\_$top$\_$features$()$ function.

Use the previously defined functions to derive your train and test datasets.

Create a loop that trains your model with an incrementally increasing number of features from the top features list.

The first pass will include the topmost important feature, the second pass will include the top two most important features and so on until the final pass of all top X features.

Your function should return a list of feature$-$based test data scores produced by the model.

TOCTask $9-$ Feature Importance, part $2(10$ Points$).$

The value of Feature Importance

This follow$-$on task will use the same RandomForestClassifier model as in your get$\_$top$\_$features$()$ function.

The new model will use a portion of the output returned by the get$\_$top$\_$features$()$ function.

Use the previously defined functions to derive your train and test datasets.

Create a loop that trains your model with an incrementally increasing number of features from the top features list.

The first pass will include the topmost important feature, the second pass will include the top two most important features and so on until the final pass of all top X features.

Your function should return a list of feature$-$based test data scores produced by the model.

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