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Dimensionality reduction is an important step in knowledge discovery in databases. Intrinsic dimension indicates the number of variables necessary to describe a data set. Two methods, box-counting… (More)
Feature selection is a critical preprocessing step in machine learning. It contributes to cost-effective model building and improvement of model prediction performance. Generally, a feature selection… (More)
OBJECTIVES This paper presents a model independent feature selection approach to identify a small subset of marker genes. METHODS AND MATERIAL An evaluation measure, minimum expected cost of… (More)
Data mining techniques have been applied to discover knowledge from large observational data sets. In this paper, we focus on mining large medical claims databases to identify high-risk patients.… (More)