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

Format:

Book

Author/Creator:

Wendler, Tilo, author.

Gröttrup, Sören, author.

Language:

English

Subjects (All):

Mathematical statistics--Data processing.

Mathematical statistics.

Data mining.

Statistics.

Computer software.

Statistics and Computing.

Data Mining and Knowledge Discovery.

Statistical Theory and Methods.

Mathematical Software.

Local Subjects:

Statistics and Computing.

Data Mining and Knowledge Discovery.

Statistical Theory and Methods.

Mathematical Software.

Physical Description:

1 online resource (1285 pages)

Edition:

2nd ed. 2021.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

Summary:

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.

Contents:

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.

ISBN:

9783030543389

3030543382