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Data Mining and Knowledge Discovery Handbook, 2 Edition part 2

Data Mining and Knowledge Discovery Handbook, 2 Edition part 2. Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavoring to accomplish. There is a lot of hidden knowledge waiting to be discovered – this is the challenge created by today’s abundance of data. Data Mining and Knowledge Discovery Handbook, 2nd Edition organizes the most current concepts, theories, standards, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery. | X Contents 10 Bayesian Networks Paola Sebastiani Maria M. Abad Marco F. Ramoni.175 11 Data Mining within a Regression Framework Richard A. Berk.209 12 Support Vector Machines Armin Shmilovici.231 13 Rule Induction Jerzy W Grzymala-Busse.249 Part III Unsupervised Methods 14 A survey of Clustering Algorithms Lior Rokach.269 15 Association Rules Frank Höppner.299 16 Frequent Set Mining Bart Goethals.321 17 Constraint-based Data Mining Jean-Francois Boulicaut Baptiste Jeudy.339 18 Link Analysis Steve Donoho .355 Part IV Soft Computing Methods 19 A Review of Evolutionary Algorithms for Data Mining Alex A. Freitas.371 20 A Review of Reinforcement Learning Methods Oded Maimon Shahar Cohen .401 21 Neural Networks For Data Mining G. Peter Zhang.419 22 Granular Computing and Rough Sets - An Incremental Development Tsau Young T. Y. Lin Churn-Jung Liau .445 23 Pattern Clustering Using a Swarm Intelligence Approach Swagatam Das Ajith Abraham .469 Contents XI 24 Using Fuzzy Logic in Data Mining Lior Rokach.505 Part V Supporting Methods 25 Statistical Methods for Data Mining Yoav Benjamini Moshe Leshno .523 26 Logics for Data Mining PetrHajek.541 27 Wavelet Methods in Data Mining Tao Li Sheng Ma Mitsunori Ogihara .553 28 Fractal Mining - Self Similarity-based Clustering and its Applications Daniel Barbara Ping Chen .573 29 Visual Analysis of Sequences Using Fractal Geometry Noa Ruschin Rimini OdedMaimon.591 30 Interestingness Measures - On Determining What Is Interesting Sigal Sahar.603 31 Quality Assessment Approaches in Data Mining Maria Halkidi Michalis Vazirgiannis.613 32 Data Mining Model Comparison Paolo Giudici .641 33 Data Mining Query Languages Jean-Francois Boulicaut Cyrille Masson .655 Part VI Advanced Methods 34 Mining Multi-label Data Grigorios Tsoumakas loannis Katakis loannis Vlahavas .667 35 Privacy in Data Mining Vicenc Torra .687 36 Meta-Learning - Concepts and Techniques Ricardo Vilalta Christophe Giraud-Carrier Pavel Brazdil.717 37 Bias vs Variance .