Feature Selection for Wine Classification
Dimensionality reduction via feature selection allows reducing the complexity of the model and avoiding overfitting. Via feature selection we select a subset of the original features, or we can apply regularization techniques.
Below are some plots showing the top features selected by different techniques.
Here we can see the relative importance of the features in the wine dataset using a random forest model.
