Data mining : theories, algorithms, and examples
Material type:
TextLanguage: English Language Series: Human factors and ergonomicsPublication details: Boca Raton Taylor & Francis 2014Description: xix, 329 P. 24 cmISBN: - 9781138073661
- 006.312 YEN
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| 006.31 RAT Statistical and machine-learning data mining : techniques for better predictive modeling and analysis of big data | 006.312 TOR Data mining with R | 006.312 WIT Data mining | 006.312 YEN Data mining : theories, algorithms, and examples | 006.32 KOS Neural networks and fuzzy systems | 006.32 RAO C++ neural network and fuzzy logic | 006.4 BIS Neural networks for pattern recognition |
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 --
Naïve 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.
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