Feature selection for classification for rare classes

1. What are the three types of feature selection methods?
2. Which classification algorithm can be used for feature selection also?
3. Does feature selection improve classification accuracy?

What are the three types of feature selection methods?

Overview. There are three types of feature selection: Wrapper methods (forward, backward, and stepwise selection), Filter methods (ANOVA, Pearson correlation, variance thresholding), and Embedded methods (Lasso, Ridge, Decision Tree).

Which classification algorithm can be used for feature selection also?

It will eliminate unimportant variables and improve the accuracy as well as the performance of classification. Random Forest has emerged as a quite useful algorithm that can handle the feature selection issue even with a higher number of variables.

Does feature selection improve classification accuracy?

The main benefit claimed for feature selection, which is the main focus in this manuscript, is that it increases classification accuracy. It is believed that removing non-informative signal can reduce noise, and can increase the contrast between labelled groups.