Includes bibliographical references (pages 338-360) and index.
Discretization of rational data / Jonathan Mugan, Klaus Truemper -- Vector DNF for datasets classification: application to the financial timing decision problem / Massimo Liquori, Andrea Scozzari -- Reducing a class of machine learning algorithms to logical commonsense reasoning operations / Xenia Naidenova -- The analysis of service quality through stated preference models and rule-based classification / Giovanni Felici, Valerio Gatta -- Support vector machines for business applications / Brian C. Lovell, Christian J. Walder -- Kernel width selection for SVM classification: A meta-learning approach / Shawkat Ali, Kate A. Smith -- Protein folding classification through multicategory discrete SVM / Carlotta Orsenigo, Carlo Vercellis -- Hierarchical profiling, scoring and applications in bioinformatics / Li Liao -- Hierarchical clustering using evolutionary algorithms / Monica Chiş -- Exploratory time series data mining by genetic clustering / T. Warren Liao -- Development of control signatures with a hybrid data mining and genetic algorithm approach Alex Burns, Shital Shah, and Andrew Kusiak -- Bayesian belief networks for data cleaning / Enrico Fagiuoli, Sara Omerino, Fabio Stella -- A comparison of revision schemes for cleaning labeling noise / Chuck P. Lam, David G. Stork -- Improving web clickstream analysis: Markov chains models and Genmax algorithms / Paolo Baldini, Paolo Giudici -- Advanced data mining and visualization techniques with probabilistic principal surfaces: application to astronomy and genetics / Antonino Staiano [and others] -- Spatial navigation assistance system for large virtual environments: the data mining approach / Mehmed Kantardzic, Pedram Sadeghian, Walaa M. Sheta -- Using grids for distributed knowledge discovery / Antonio Congiusta, Domenico Talia, Paolo Trunfio Fuzzy miner: extracting fuzzy rules from numerical patterns / Nikos Pelekis [and others] --Routing attribute data mining based on rough set theory / Yanbing Liu, Menghao Wang, Hong Tang.
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"This book focuses on the mathematical models and methods that support most data mining applications and solution techniques, covering such topics as association rules; Bayesian methods; data visualization; kernel methods; neural networks; text, speech, and image recognition; an invaluable resource for scholars and practitioners in the fields of biomedicine, engineering, finance, manufacturing, marketing, performance measurement, and telecommunications"--Provided by publisher.
Mathematical methods for knowledge discovery and data mining.
1599045281
Idea Group
Data mining-- Mathematical models.
Data mining.
Knowledge acquisition (Expert systems)
Acquisition des connaissances (Systèmes experts)
Exploration de données (Informatique)
Exploration de données (Informatique)-- Modèles mathématiques.