Contemporary perspectives in data mining. Volume 1 / edited by Kenneth D. Lawrence, Ronald K. Klimberg.

Online resource; title from PDF title page (EBSCO, viewed July 10, 2017).

Includes bibliographical references.

Machine generated contents note: SECTION A METHODOLOGICAL STUDIES -- 1. Frame Selection Based on Mixtures of Trees in Discrete Data / Zhimin Huang -- 2. Data Mining Techniques for Quality Improvement / Seoung Bum Kim -- 3. Big Bang Data Generation: Reinforcement for the Discriminant Problem / Gregory Smith -- 4. Business Analytics -- Today's Green? / B.D. McCullough -- 5. Change Point Plots: A Graphical Method for Identifying Changes in the Distribution of a Random Variable Over Time / James J. Cochran -- SECTION B FINANCIAL STUDIES -- 6. Discovering the Co-movement Structure of Chinese Stock Market by SPACE with EM Algorithm / Zhimin Huang -- 7. Knowledge Discovery for Continuous Financial Assurance Using Multiple Types of Digital Information / Daniel E. O'Leary -- 8. Regression Estimation of a Cost Function with Severe Data Problems and Extreme Values of Observations in the Maintenance and Repair Activities of Backbone Internet Providers / Sheila M. Lawrence -- SECTION C BEHAVIORAL STUDIES -- 9. Data Mining's Usefulness For Assessing Market Segmentation Performance / James Mangiameli -- 10. Measuring the Semantic and Representational Consistency of Interconnected Structured and Unstructured Data for Data Mining Applications / Paul Mangiameli -- 11. Clustering and Principal Components Analyses to Understand Student Motivations and Ethical Approaches to Academic Ethics with Recommendations for Curricular Change / Kathleen Campbell.

eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - Worldwide