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.