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Training
Predictive Modeling using Enterprise Miner Software
Audience
This Level III course is the foundation for further courses in
the data mining curriculum. It is designed to give data
analysts the necessary skills to build successful predictive
models.
Benefits
This course provides the skills to build effective predictive
models using Enterprise Miner. Methods for overcoming
common data mining challenges are illustrated on actual
business data.
After completing this course, you should be able to
- build, tune, and deploy categorical and continuous
predictive models
- evaluate the effectiveness of competing models
- recognize the strengths and limitations of various
modeling approaches
- explain modeling results to business analysts.
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 Getting Started
with SAS Software: A Non-programming Approach
course.
Course Topics
Introduction to Predictive Modeling
- formulating analysis objective
- preparing an Enterprise Miner project
- constructing a simple predictive models
- adjusting predictions
- optimizing predictive decisions
- comparing predictive models
- deploying predictive models
Predictive Algorithms
- constructing tree models
- adjusting tree models
- aggregating tree models
- using memory based reasoning
Parametric Models
- enhancing logistic regression models
- constructing multilayer perceptrons
- tuning multilayer perceptrons
- using alternative parametric models
Interval Target Models
- constructing regression trees
- constructing interval parametric models
- combining classification and regression models
Model Interpretation
- explaining model results
- defining response segments
- creating customized model assessment measures
Software Addressed
This course covers Version 4 of Enterprise Miner software.
Course Materials
You receive Predictive Modeling Using Enterprise Miner
Software Course Notes.
To order additional copies of the course notes, visit our
online Publications Catalog.
| Duration: 2.5 days
| CEUs: 1.5
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What participants say about the M-series:
"The educational content, exchange of ideas, and intellectual environment
I found at the conference exceeded my expectations and confirmed SAS'
place as the premier data mining conference in the world."
~~~~~~~~~
"Right time. Right place. Right content."
~~~~~~~~~
"This was a superb environment - one of the smartest conference venues I
have experienced (and I have experienced a lot). The talks went into
greater depth than the talks at many such meetings. Many of the talks were
particularly valuable in shedding light on different application areas of
data mining."
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