UID:
almahu_9949070725402882
Format:
XV, 1274 p. 1541 illus.
,
online resource.
Edition:
2nd ed. 2021.
ISBN:
9783030543389
Content:
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.
Note:
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.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783030543372
Additional Edition:
Printed edition: ISBN 9783030543396
Language:
English
DOI:
10.1007/978-3-030-54338-9
URL:
https://doi.org/10.1007/978-3-030-54338-9
