A data envelopment analysis-based approach for data preprocessing

被引：29

作者：

Pendharkar, PC ^{[1
]}

机构：

[1] Penn State Univ, Capital Coll, Sch Business Adm, Middletown, PA 17057 USA

来源：

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING | 2005年 / 17卷 / 10期

关键词：

data envelopment analysis; artificial neural networks; data preprocessing;

D O I：

10.1109/TKDE.2005.155

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1379 / 1388

页数：10

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