Nong Ye

Data Mining (eBook, ePUB)

Theories, Algorithms, and Examples

• Format: ePub

Produktbeschreibung

New technologies have enabled us to collect massive amounts of data in many fields. However, our pace of discovering useful information and knowledge from these data falls far behind our pace of collecting the data. Data Mining: Theories, Algorithms, and Examples introduces and explains a comprehensive set of data mining algorithms from various dat

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 349
• Erscheinungstermin: 26. Juli 2013
• Englisch
• ISBN-13: 9781482219388
• Artikelnr.: 58130857

Autorenporträt

Nong Ye is Professor of Industrial Engineering at Arizona State University in Tempe.

Inhaltsangabe

AN OVERVIEW OF DATA MINING METHODOLOGIES: Introduction to data mining
methodologies. METHODOLOGIES FOR MINING CLASSIFICATION AND PREDICTION
PATTERNS: Regression models. Bayes classifiers. Decision trees. Multi-layer
feedforward artificial neural networks. Support vector machines. Supervised
clustering. METHODOLOGIES FOR MINING CLUSTERING AND ASSOCIATION PATTERNS:
Hierarchical clustering. Partitional clustering. Self-organized map.
Probability distribution estimation. Association rules. Bayesian networks.
METHODOLOGIES FOR MINING DATA REDUCTION PATTERNS: Principal components
analysis. Multi-dimensional scaling. Latent variable analysis.
METHODOLOGIES FOR MINING OUTLIER AND ANOMALY PATTERNS: Univariate control
charts. Multivariate control charts. METHODOLOGIES FOR MINING SEQUENTIAL
AND TIME SERIES PATTERNS: Autocorrelation based time series analysis.
Hidden Markov models for sequential pattern mining. Wavelet analysis.
Hilbert transform. Nonlinear time series analysis.