Hybrid approaches for classification under information acquisition cost constraint

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

We address a problem of classification with information acquisition cost constraint (CIACC). The objective of the CIACC problem is to develop a classification function that maximizes correct classifications under the user defined information acquisition cost constraint. We propose hybrid simulated annealing and neural network (SA-ANN), and tabu search and neural network (TS-ANN) procedures to solve the CIACC problem. Using simulated and a real-world data set from medical domain, we show that the proposed hybrid procedures solve the CIACC problem. The results of our experiments indicate that the performance of hybrid approaches is sensitive to the data distribution, and memory-based hybrid tabu search approaches may perform as good as or better than probabilistic hybrid simulated annealing approach.

Original languageEnglish (US)
Pages (from-to)228-241
Number of pages14
JournalDecision Support Systems
Volume41
Issue number1
DOIs
StatePublished - Nov 1 2005

Fingerprint

Costs and Cost Analysis
Taboo
Costs
Tabu search
Simulated annealing
Neural networks
Information acquisition
Hybrid approach
Data storage equipment
Experiments
Neural Networks
Annealing

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Information Systems
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Information Systems and Management

Cite this

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Hybrid approaches for classification under information acquisition cost constraint. / Pendharkar, Parag C.

In: Decision Support Systems, Vol. 41, No. 1, 01.11.2005, p. 228-241.

Research output: Contribution to journalArticle

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