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Data Mining with SPSS Modeler : Theory, Exercises and Solutions / / by Tilo Wendler, Sören Gröttrup



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Autore: Wendler Tilo Visualizza persona
Titolo: Data Mining with SPSS Modeler : Theory, Exercises and Solutions / / by Tilo Wendler, Sören Gröttrup Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
Edizione: 2nd ed. 2021.
Descrizione fisica: 1 online resource (1285 pages)
Disciplina: 006.312
Soggetto topico: Mathematical statistics - Data processing
Data mining
Statistics
Computer software
Statistics and Computing
Data Mining and Knowledge Discovery
Statistical Theory and Methods
Mathematical Software
Persona (resp. second.): GröttrupSören
Nota di contenuto: 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.
Sommario/riassunto: 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.
Titolo autorizzato: Data Mining with SPSS Modeler  Visualizza cluster
ISBN: 9783030543389
3030543382
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910484742203321
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