Applied Data Mining for Forecasting Using SAS. Tim Rey
The correct bibliographic citation for this manual is as follows: Rey, Tim, Arthur Kordon, and Chip Wells. 2012. Applied Data Mining for Forecasting Using SAS®. Cary, NC: SAS Institute Inc.
Applied Data Mining for Forecasting Using SAS®
Copyright © 2012, SAS Institute Inc., Cary, NC, USA
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Contents
Chapter 1 Why Industry Needs Data Mining for Forecasting
1.2 Forecasting Capabilities as a Competitive Advantage
1.3 The Explosion of Available Time Series Data
1.4 Some Background on Forecasting
1.5 The Limitations of Classical Univariate Forecasting
1.6 What is a Time Series Database?
1.7 What is Data Mining for Forecasting?
1.8 Advantages of Integrating Data Mining and Forecasting
Chapter 2 Data Mining for Forecasting Work Process
2.3 Work Process with SAS Tools
2.3.1 Data Preparation Steps with SAS Tools
2.3.2 Variable Reduction and Selection Steps with SAS Tools
2.3.3 Forecasting Steps with SAS Tools
2.3.4 Model Deployment Steps with SAS Tools
2.3.5 Model Maintenance Steps with SAS Tools
2.3.6 Guidance for SAS Tool Selection Related to Data Mining in Forecasting
2.4 Work Process Integration in Six Sigma
2.4.3 Integration with the DMAIC Process
Chapter 3 Data Mining for Forecasting Infrastructure
3.2.1 Personal Computers Network Infrastructure
3.2.2 Client/Server Infrastructure
3.2.3 Cloud Computing Infrastructure