Decomposition in Data Mining A Medical Case Study.pdfVIP

Decomposition in Data Mining: A Medical Case Study Andrew Kusiak Intelligent Systems Laboratory 4312 Seamans Center The University of Iowa Iowa City, Iowa 52242 ñ 1527 andrew-kusiak@ /~ankusiak ABSTRACT Decomposition is a tool for managing complexity in data mining and enhancing the quality of knowledge extracted form large databases. A typology of decomposition approaches applicable to data mining is presented. One of the decomposition approaches, the structured rule-feature matrix, is used as the backbone of a system for informed decision-making. Such a system can be implemented as a decision table, a decision map, or a decision atlas. The ideas presented in the paper are illustrated with examples and a medical case study. Keywords: Data mining, decision making, decomposition, rule structuring, disease diagnosis, lung cancer. 1. INTRODUCTION Data mining is concerned with discovery of patterns, associations, rules, and other forms of knowledge in data sets. This knowledge is automatically extracted from data rather than being formulated by a user as it is done in traditional modeling approaches, e.g., statistical or optimization modeling. As a new discipline, data mining draws from other areas such as statistics, machine learning, database retrieval, pattern recognition, and high performance computing. In many applications, data is automatically generated and therefore