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＜電子ブック＞
Data Mining with SPSS Modeler : Theory, Exercises and Solutions / by Tilo Wendler, Sören Gröttrup

版	2nd ed. 2021.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2021
大きさ	XV, 1274 p. 1541 illus : online resource
著者標目	*Wendler, Tilo author Gröttrup, Sören author SpringerLink (Online service)
件　名	LCSH:Mathematical statistics—Data processing LCSH:Data mining LCSH:Statistics  LCSH:Computer software FREE:Statistics and Computing FREE:Data Mining and Knowledge Discovery FREE:Statistical Theory and Methods FREE:Mathematical Software
一般注記	Preface -- Introduction -- Basic Functions of the SPSS Modeler -- Univariate Statistics -- Multivariate Statistics -- Regression Models -- Factor Analysis -- Cluster Analysis -- Classification Models -- Using R with the Modeler -- Imbalanced Data and Resampling Techniques -- Case Study: Fault Detection in Semiconductor Manufacturing Process -- Appendix Now in its second edition, this textbook introduces readers to the IBM SPSS Modeler and guides them through data mining processes and relevant statistical methods. Focusing on step-by-step tutorials and well-documented examples that help demystify complex mathematical algorithms and computer programs, it also features a variety of exercises and solutions, as well as an accompanying website with data sets and SPSS Modeler streams. While intended for students, the simplicity of the Modeler makes the book useful for anyone wishing to learn about basic and more advanced data mining, and put this knowledge into practice. This revised and updated second edition includes a new chapter on imbalanced data and resampling techniques as well as an extensive case study on the cross-industry standard process for data mining HTTP:URL=https://doi.org/10.1007/978-3-030-54338-9

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