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Produktbild: Fernandez, G: Data Mining Using SAS Applications

Fernandez, G: Data Mining Using SAS Applications

Fr. 103.00

inkl. gesetzl. MwSt., Versandkostenfrei

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.01.2002

Abbildungen

136 schwarzweisse Abbildungen

Verlag

Springer

Seitenzahl

367

Maße (L/B/H)

23.5/15.5/2 cm

Gewicht

587 g

Auflage

2003

Sprache

Englisch

ISBN

978-1-58488-345-6

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.01.2002

Abbildungen

136 schwarzweisse Abbildungen

Verlag

Springer

Seitenzahl

367

Maße (L/B/H)

23.5/15.5/2 cm

Gewicht

587 g

Auflage

2003

Sprache

Englisch

ISBN

978-1-58488-345-6

Herstelleradresse

Springer Heidelberg
Tiergartenstr. 17
69121 Heidelberg
DE
buchhandel-buch@springer.com

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  • Produktbild: Fernandez, G: Data Mining Using SAS Applications
  • DATA MINING - A GENTLE INTRODUCTION Data Mining: Why Now? Benefits of Data Mining Data Mining: Users Data Mining Tools Data Mining Steps Problems in Data Mining Process SAS Software: The Leader in Data Mining User-Friendly SAS Macros for Data Mining PREPARING DATA FOR DATA MINING Data Requirements in Data Mining Ideal Structures of Data for Data Mining Understanding the Measurement Scale of Variables Entire Database vs. Representative Sample Sampling for Data Mining SAS Applications Used in Data Preparation EXPLORATORY DATA ANALYSIS Exploring Continuous Variable Data Exploration: Categorical Variable SAS Macro Applications Used in Data Exploration UNSUPERVISED LEARNING METHODS Applications of Unsupervised Learning Methods Principal Component Analysis (PCA) Exploratory Factor Analysis (EFA) Disjoint Cluster Analysis (DCA) Bi-Plot Display of PCA, EFA, and DCA Results PCA And EFA Using SAS Macro FACTOR Disjoint Cluster Analysis Using SAS Macro DISJCLUS SUPERVISED LEARNING METHODS: PREDICTION Applications of Supervised Predictive Methods Multiple Linear Regression Modeling Binary Linear Regression Modeling Multiple Linear Regression Using SAS Macro REGDIAG Lift Chart Using SAS Macro LIFT Scoring New Regression Data Using the SAS Macro RSCORE Logistic Regression Using SAS Macro LOGISTIC Scoring New Logistic Regression Data Using the SAS Macro LSCORE Case Study 1: Modeling Multiple Linear Regression Case Study 2: Modeling Multiple Linear Regression with Categorical Variables Case Study 3: Modeling Binary Logistic Regression SUPERVISED LEARNING METHODS: CLASSIFICATION Discriminant Analysis Stepwise Discriminant Analysis Canonical Discriminant Analysis (CDA) Discriminant Function Analysis (DFA) Applications of Discriminant Analysis Classification Tree Based on CHAID Applications of CHAID Discriminant Analysis Using SAS Macro DISCRIM Decison Tree Using SAS Macro 'CHAID' Case Study1: CDA and Parametric DFA Case Study2: Non-Parametric DFA Case Study3: Classification Tree Using CHAID EMERGING TECHNOLOGIES IN DATA MINING Data Warehousing Artificial Neural Network Methods Market Basket Analysis SAS Software: The Leader in Data Mining APPENDIX: INSTRUCTION FOR USING THE SAS MACROS INDEX Each chapter also contains an introduction, a summary, references, list of figures, and suggested further reading. Short TOC