A data envelopment analysis-based approach for data preprocessing

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

In this paper, we show how the data envelopment analysis (DEA) model might be useful to screen training data so a subset of examples that satisfy monotonicity property can be identified. Using real-world health care and software engineering data, managerial monotonicity assumption, and artificial neural network (ANN) as a forecasting model, we illustrate that DEA-based data screening of training data improves forecasting accuracy of an ANN.

Original languageEnglish (US)
Pages (from-to)1379-1388
Number of pages10
JournalIEEE Transactions on Knowledge and Data Engineering
Volume17
Issue number10
DOIs
StatePublished - Oct 1 2005

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Data envelopment analysis
Neural networks
Health care
Software engineering
Screening

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

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A data envelopment analysis-based approach for data preprocessing. / Pendharkar, Parag C.

In: IEEE Transactions on Knowledge and Data Engineering, Vol. 17, No. 10, 01.10.2005, p. 1379-1388.

Research output: Contribution to journalArticle

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