Data mining for business analytics : concepts, techniques, and applications in JMP Pro
Galit Shmueli ... [et al.]
- Hoboken, N.J. : John Wiley & Sons, c2017.
- xxii, 442 p. : ill. ; 26 cm.
Includes index.
Overview of the data mining process -- Data visualization -- Dimension reduction -- Evaluating predictive performance -- Multiple linear regression -- K-nearest neighbors (kNN) -- The naive Bayes classifier -- Classification and regression trees -- Logistic regression -- Neural nets -- Discriminant analysis -- Combining methods : ensembles and uplift modeling -- Cluster analysis -- Handling time series -- Regression-based forecasting -- Smoothing methods -- Cases.
Featuring hands–on applications with JMP Pro®, a statistical package from the SAS Institute, the book uses engaging, real–world examples to build a theoretical and practical understanding of key data mining methods, especially predictive models for classification and prediction. Topics include data visualization, dimension reduction techniques, clustering, linear and logistic regression, classification and regression trees, discriminant analysis, naive Bayes, neural networks, uplift modeling, ensemble models, and time series forecasting.
9781118877432
2015048305
Business mathematics--Computer programs Business--Data processing Data mining Computers--general