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Predictive Modeling Using SAS Enterprise Miner 5.1
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Duration: 3.0 days CEUs: 1.8 | ||
| (This course is not currently scheduled.) |
This outline is provisional and subject to change.
This course gives you the skills that are necessary to build successful predictive models using SAS Enterprise Miner 5 in SAS 9. This course is the foundation for further courses in the data mining curriculum.
Learn how to use Enterprise Miner 5 software to
- build predictive models, including regression models, decision trees, and neural networks
- determine the appropriate model to ensure good model generalization
- compare different models using graphical and numerical assessment measures
- deploy a predictive model to score new data
- apply decision trees as a tool to tackle analytical challenges like variable selection
- add flexibility to a standard regression model.
Who should attend
Modelers, analysts, and statisticians who generate predictive models and who have access to Enterprise Miner 5
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Prerequisites
Before attending this course, you should
- be familiar with simple regression modeling concepts
- have some experience with creating and managing SAS data sets, which you can gain from the Introduction to Programming Concepts Using SAS Software or the SAS Programming I: Essentials course.
Course Contents
Introduction to Predictive Modeling
- formulating an analysis objective
- preparing an Enterprise Miner project
- constructing a simple predictive model
- adjusting predictions
- optimizing predictive decisions
- tuning a regression model
- comparing predictive models
- deploying predictive models
- enhancing logistic regression models
- constructing multilayer perceptrons
- tuning multilayer perceptrons
- using alternative parametric models
- constructing tree models
- adjusting tree models
- aggregating tree models
Software
This course addresses SAS Enterprise Miner.
Course Materials
Students receive a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.
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Available for on-site training or can be scheduled at any SAS training facility
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