Buch, Englisch, Band 6, 748 Seiten, Format (B × H): 164 mm x 245 mm, Gewicht: 1320 g
Reihe: Massive Computing
Buch, Englisch, Band 6, 748 Seiten, Format (B × H): 164 mm x 245 mm, Gewicht: 1320 g
Reihe: Massive Computing
ISBN: 978-0-387-34294-8
Verlag: Springer Us
This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications. Most theoretical developments are accompanied by extensive empirical analysis, offering a deep insight into both theoretical and practical aspects of the subject. The book presents the combined research experiences of 40 expert contributors of world renown.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
A Common Logic Approach to Data Mining and Pattern Recognition.- The One Clause at a Time (OCAT) Approach to Data Mining and Knowledge Discovery.- An Incremental Learning Algorithm for Inferring Logical Rules from Examples in the Framework of the Common Reasoning Process.- Discovering Rules That Govern Monotone Phenomena.- Learning Logic Formulas and Related Error Distributions.- Feature Selection for Data Mining.- Transformation of Rational Data and Set Data to Logic Data.- Data Farming: Concepts and Methods.- Rule Induction Through Discrete Support Vector Decision Trees.- Multi-Attribute Decision Trees and Decision Rules.- Knowledge Acquisition and Uncertainty in Fault Diagnosis: A Rough Sets Perspective.- Discovering Knowledge Nuggets with a Genetic Algorithm.- Diversity Mechanisms in Pitt-Style Evolutionary Classifier Systems.- Fuzzy Logic in Discovering Association Rules: An Overview.- Mining Human Interpretable Knowledge with Fuzzy Modeling Methods: An Overview.- Data Mining from Multimedia Patient Records.- Learning to Find Context Based Spelling Errors.- Induction and Inference with Fuzzy Rules for Textual Information Retrieval.- Statistical Rule Induction in the Presence of Prior Information: The Bayesian Record Linkage Problem.- Some Future Trends in Data Mining.
