Inductive, evolutionary, and neural computing techniques for discrimination

A comparative study

Siddhartha Bhattacharyya, Parag C. Pendharkar

Research output: Contribution to journalArticle

54 Citations (Scopus)

Abstract

This paper provides a comparative study of machine learning techniques for two-group discrimination. Simulated data is used to examine how the different learning techniques perform with respect to certain data distribution characteristics. Both linear and nonlinear discrimination methods are considered. The data has been previously used in the comparative evaluation of a number of techniques and helps relate our findings across a range of discrimination techniques.

Original languageEnglish (US)
Pages (from-to)871-898
Number of pages28
JournalDecision Sciences
Volume29
Issue number4
StatePublished - Sep 1 1998

Fingerprint

Learning systems
Comparative study
Discrimination
Evolutionary

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Strategy and Management
  • Information Systems and Management
  • Management of Technology and Innovation

Cite this

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Inductive, evolutionary, and neural computing techniques for discrimination : A comparative study. / Bhattacharyya, Siddhartha; Pendharkar, Parag C.

In: Decision Sciences, Vol. 29, No. 4, 01.09.1998, p. 871-898.

Research output: Contribution to journalArticle

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