Data mining. Theories, algorithms, and examples

✍ Scribed by Ye, Nong

Publisher: CRC Press
Year: 2014
Tongue: English
Leaves: 347
Series: Human factors and ergonomics
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

Content: AN OVERVIEW OF DATA MINING METHODOLOGIESIntroduction to data mining methodologiesMETHODOLOGIES FOR MINING CLASSIFICATION AND PREDICTION PATTERNSRegression modelsBayes classifiersDecision treesMulti-layer feedforward artificial neural networksSupport vector machinesSupervised clusteringMETHODOLOGIES FOR MINING CLUSTERING AND ASSOCIATION PATTERNSHierarchical clusteringPartitional clusteringSelf-organized mapProbability distribution estimationAssociation rulesBayesian networksMETHODOLOGIES FOR MINING DATA REDUCTION PATTERNSPrincipal components analysisMulti-dimensional scalingLatent variable analysisMETHODOLOGIES FOR MINING OUTLIER AND ANOMALY PATTERNSUnivariate control chartsMultivariate control chartsMETHODOLOGIES FOR MINING SEQUENTIAL AND TIME SERIES PATTERNSAutocorrelation based time series analysisHidden Markov models for sequential pattern miningWavelet analysisHilbert transformNonlinear time series analysis

✦ Subjects

Data mining.;Data mining -- Mathematical models.

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