Bibliograph

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

Type

Label

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

Language

eng

resource.imageBitDepth

Literary Form

non fiction

Main title

Data Mining with SPSS Modeler

Medium

electronic resource

Nature of contents

dictionaries

Oclc number

1255236319

Responsibility statement

by Tilo Wendler, Sören Gröttrup

Series statement

Springer eBooks.

Sub title

Theory, Exercises and Solutions

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.--, Provided by publisher

Table Of 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

Classification

Contributor