Advanced Predictive Modeling Using SAS® Enterprise Miner™
PMAD : PMA42
This course covers advanced topics using SAS Enterprise Miner, including how to optimize the performance of predictive models beyond the basics. The course continues the development of predictive models that begins in the Applied Analytics Using SAS Enterprise Miner course, for example, by making use of the two-stage modeling node. In addition, some of the newest modeling nodes and latest variable selection methods are covered. Tips for working in an efficient way with SAS Enterprise Miner complete the course.
The self-study e-learning includes:
The self-study e-learning includes:
- Annotatable course notes in PDF format.
- Virtual lab time to practice.
Who Should Attend
Advanced predictive modelers who use SAS Enterprise Miner
Prerequisites
Before attending this course, it is recommended that you:
- Have completed the Applied Analytics Using SAS Enterprise Miner course.
- Have some experience with creating and managing SAS data sets, which you can gain from the SAS Programming 1: Essentials course.
- Have some experience building statistical models using SAS/STAT software.
- Have completed a statistics course that covers linear regression and logistic regression.
SAS Products Covered
SAS Enterprise Miner
Course Outline
SAS Enterprise Miner Prediction Fundamentals
- SAS Enterprise Miner prediction setup.
- Prediction basics.
- Constructing a decision tree predictive model.
- Running the regression node.
- Training a neural network.
- Comparing models with summary statistics.
- Describe principal component analysis.
- Describe variable clustering.
- Explain how to use partial least squares regression in SAS Enterprise Miner.
- Using LAR/LASSO for variable selection.
- Implementing categorical input recoding.
- Creating empirical logit plots.
- Implementing all subsets regression.
- Describe the basics of support vector machines.
- Using the HP Forest node in SAS Enterprise Miner to fit a forest model.
- Modeling rare events.
- Using the Rule Induction node in SAS Enterprise Miner.
- Appraising model performance.
- Defining a generalized profit matrix.
- Creating generalized assessment plots.
- Using the Two-Stage Model node.
- Constructing component models.
- Using the Open Source Integration node.
- Reusing metadata.
- Importing and using external models (self-study).
Live Class Schedule
Duration: 30 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
Live Class Schedule
SOLD SEPARATELY
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.