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Data mining with SPSS modelertheory,...

Grottrup, Soren.

Data mining with SPSS modelertheory, exercises and solutions /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data mining with SPSS modelerby Tilo Wendler, Soren Grottrup.
Reminder of title:	theory, exercises and solutions /
Author:	Wendler, Tilo.
other author:	Grottrup, Soren.
Published:	Cham :Springer International Publishing :2021.
Description:	xv, 1274 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Data mining.
Online resource:	https://doi.org/10.1007/978-3-030-54338-9
ISBN:	9783030543389$q(electronic bk.)

Data mining with SPSS modelertheory, exercises and solutions /
Wendler, Tilo.

Data mining with SPSS modelertheory, exercises and solutions /[electronic resource] :by Tilo Wendler, Soren Grottrup. - Second edition. - Cham :Springer International Publishing :2021. - xv, 1274 p. :ill., digital ;24 cm.

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.

ISBN: 9783030543389$q(electronic bk.)

Standard No.: 10.1007/978-3-030-54338-9doiSubjects--Uniform Titles:

SPSS (Computer file)
Subjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343 / W4 2021

Dewey Class. No.: 006.312

Data mining with SPSS modelertheory, exercises and solutions /
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245 1 0 $a Data mining with SPSS modeler $h [electronic resource] : $b theory, exercises and solutions / $c by Tilo Wendler, Soren Grottrup.
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300 $a xv, 1274 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
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650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Statistical Theory and Methods. $3 274054
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950 $a Mathematics and Statistics (SpringerNature-11649)