Papers
Topics
Authors
Recent
2000 character limit reached

FSinR: an exhaustive package for feature selection (2002.10330v1)

Published 24 Feb 2020 in cs.LG and stat.ML

Abstract: Feature Selection (FS) is a key task in Machine Learning. It consists in selecting a number of relevant variables for the model construction or data analysis. We present the R package, FSinR, which implements a variety of widely known filter and wrapper methods, as well as search algorithms. Thus, the package provides the possibility to perform the feature selection process, which consists in the combination of a guided search on the subsets of features with the filter or wrapper methods that return an evaluation measure of those subsets. In this article, we also present some examples on the usage of the package and a comparison with other packages available in R that contain methods for feature selection.

Citations (13)

Summary

We haven't generated a summary for this paper yet.

Whiteboard

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.