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A data envelopment analysis-based approach for data preprocessing

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1 Author(s)
Pendharkar, P.C. ; Pennsylvania State Univ., Middletown, PA, USA

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.

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Knowledge and Data Engineering, IEEE Transactions on  (Volume:17 ,  Issue: 10 )