Instance Selection and Construction for Data Mining

This volume serves as a comprehensive reference for graduate students, practitioners and researchers in KDD to report new developments and applications, to share hard-learned experiences in order to avoid similar pitfalls, and to shed light on the future development of instance selection.

Abstract

The ability to analyze and understand massive data sets lags far behind the ability to gather and store the data. To meet this challenge, knowledge discovery and data mining (KDD) is growing rapidly a