Selection of Relevant Features in Machine Learning.

Abstract

In this paper, we review the problem of selecting relevant features for use in machine learning. We describe this problem in terms of heuristic search through a space of feature sets, and we identify four dimensions along which approaches to the problem can vary. We consider recent work on feature selection in terms of this framework, then close with some challenges for future work in the area.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1994
Accession Number
ADA292575

Entities

People

  • Pat Langley

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Algorithms
  • Applied Computer Science
  • Artificial Intelligence
  • Artificial Intelligence Computing
  • Classification
  • Computer Science
  • Consistency
  • Cybersecurity
  • Data Science
  • Data Sets
  • Feature Selection
  • Learning
  • Machine Learning
  • Neural Networks
  • New Brunswick

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Space