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Improving Knowledge Discovery Through the Integration of Data Mining Techniques (Hardcover)

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Targeting academicians, researchers, advanced-level students, decision-makers, and business professionals, this book contributes to the field and explores the tools and techniques of improving knowledge discovery using diverse data mining methods. It covers a wide range of state-of-the-art research in this rapidly growing area and has applications to many real world problems, including farming and food production, healthcare, finance, and hazards aversion. Divided into four untitled sections, sixteen chapters are: integration of data mining and statistical methods for constructing and exploring data cubes; online processing of end-user data in real-time data warehousing; multi-relational data mining; comparative study of incremental learning algorithms in multidimensional outlier detection on data stream; advances of applying metaheuristics to data mining techniques; artificial immune optimization algorithm; the role of hypermutation and affinity maturation in AIS approaches to clustering; cancer pathway network analysis using cellular automata; knowledge extraction from information system using rough computing; data mining techniques on earthquake data; an evaluation of C4.5 and Fuzzy C4.5 with effect of pruning methods; an empirical evaluation of feature selection methods; data mining driven rule based expert system for medical billing compliance; a web backtracking technique for fraud detection in financial applications; segmentation of crops and weeds using supervised learning technique; a supervised learning model for AGV perception in unstructured environment. Annotation ©2015 Ringgold, Inc., Portland, OR (protoview.com)
Number of Pages: 392
Genre: Computers + Internet, Language + Art + Disciplines
Sub-Genre: Database Management / Data Mining
Format: Hardcover
Publisher: Igi Global
Language: English
Street Date: August 31, 2015
TCIN: 18849057
UPC: 9781466685130
Item Number (DPCI): 247-48-2316

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