Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

Feature selection

Known as: Feature selection problem, Input selection, Feature subset selection 
In machine learning and statistics, feature selection, also known as variable selection, attribute selection or variable subset selection, is the… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2019
Review
2019
Abstract Ensemble learning is a prolific field in Machine Learning since it is based on the assumption that combining the output… Expand
Is this relevant?
Highly Cited
2005
Highly Cited
2005
In supervised learning scenarios, feature selection has been studied widely in the literature. Selecting features in unsupervised… Expand
  • figure 1
  • figure 2
  • figure 3
  • table 1
Is this relevant?
Highly Cited
2003
Highly Cited
2003
Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or… Expand
Is this relevant?
Highly Cited
2003
Highly Cited
2003
A central problem in machine learning is identifying a representative set of features from which to construct a classification… Expand
  • table 2.1
  • table 2.2
  • figure 2.1
  • table 2.3
  • figure 3.1
Is this relevant?
Highly Cited
2002
Highly Cited
2002
In this article, we describe an unsupervised feature selection algorithm suitable for data sets, large in both dimension and size… Expand
Is this relevant?
Highly Cited
1997
Highly Cited
1997
Abstract In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset… Expand
  • figure I
  • table 1
  • figure 2
  • figure 3
  • figure 4
Is this relevant?
Highly Cited
1997
Highly Cited
1997
This paper is a comparative study of feature selection methods in statistical learning of text categorization The focus is on… Expand
  • figure 2
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
1996
Highly Cited
1996
In this paper, we examine a method for feature subset selection based on Information Theory. Initially, a framework for defining… Expand
  • figure 1
  • table 1
  • table 2
  • table 3
Is this relevant?
Highly Cited
1994
Highly Cited
1994
Sequential search methods characterized by a dynamically changing number of features included or eliminated at each step… Expand
  • figure 1
  • figure 2
Is this relevant?
Highly Cited
1992
Highly Cited
1992
In real-world concept learning problems, the representation of data often uses many features, only a few of which may be related… Expand
Is this relevant?