Mining Data Envelopment Analysis using Clustering Approach
for Heterogeneous Decision Making Units
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This book integrates two important fields of information technology, data mining and data envelopment analysis (DEA), to provide a new tool for measuring the performance of decision making units (DMU). Many investigations have dealt with the DEA models, but few have focused on heterogeneous DMUs, outlier detection, and scalability over large data sets. In this book, a comprehensive model is presented. A constraint based clustering method is introduced for early detection of outliers to evaluate the performance scores of non homogeneous DMUs. The book includes the different preprocessing stages...
This book integrates two important fields of information technology, data mining and data envelopment analysis (DEA), to provide a new tool for measuring the performance of decision making units (DMU). Many investigations have dealt with the DEA models, but few have focused on heterogeneous DMUs, outlier detection, and scalability over large data sets. In this book, a comprehensive model is presented. A constraint based clustering method is introduced for early detection of outliers to evaluate the performance scores of non homogeneous DMUs. The book includes the different preprocessing stages used in applying different approaches of data mining. Along with the theory, an extensive analysis in assessing the transportation system funding for school districts in the state of North Dakota is provided. This book is originally a Ph.D. dissertation at NDSU,Fargo, ND, USA.
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