Data mining : theories, algorithms, and examples /
Nong Ye
- Boca Raton : Taylor & Francis, [2014]
- xix, 329 p. ; 24 cm.
- Human Factors and Ergonomics Series .
- Human Factors and Ergonomics Series .
"A CRC title."
Includes bibliographical references and index
pt. 1. An overview of data mining. Introduction to data, data patterns, and data mining -- pt. 2. Algorithms for mining classification and prediction patterns. Linear and nonlinear regression models -- Naive Bayes classifier -- Decision and regression trees -- Artificial neural networks for classification and prediction -- Support vector machines -- k-Nearest neighbor classifier and supervised clustering -- pt. 3. Algorithms for mining cluster and association patterns. Hierarchial clustering -- K-Means clustering and density-based clustering -- Self-organizing map -- Probability distributions of univariate data -- Association rules -- Bayesian network -- pt. 4. Algorithms for mining data reduction patterns. Principal component analysis -- Multidimensional scaling -- pt. 5. Algorithms for mining outlier and anomaly patterns. Univariate control charts -- Multivariate control charts -- pt. 6. Algorithms for mining sequential and temporal patterns. Autocorrelation and time series analysis -- Markov chain models and hidden Markov models -- Wavelet analysis