A data envelopment analysis-based approach for data preprocessing

A data envelopment analysis-based approach for data preprocessing

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 ne...

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Veröffentlicht in:IEEE transactions on knowledge and data engineering 2005-10, Vol.17 (10), p.1379-1388
1. Verfasser: Pendharkar, P.C.
Format: Artikel
Sprache:eng
Schlagworte:
Applied sciences
Artificial neural networks
Computer science
control theory
systems
Data analysis
Data envelopment analysis
Data preprocessing
Engineering management
Exact sciences and technology
Forecasting
Health care
Index Terms- Data envelopment analysis
Information systems. Data bases
Learning theory
Management training
Mathematical models
Medical services
Memory organisation. Data processing
Neural networks
Operations research
Predictive models
Preprocessing
Software
Software engineering
Training
Training data
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Beschreibung
Zusammenfassung: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.
ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2005.155