Presented by Prof. Dr. Christina Andersson, Frankfurt University of Applied Sciences

This course imparts knowledge about the functionality of SAS Enterprise Miner. You learn further techniques of predictive modeling for classification and regression by using some of the newer modeling nodes. Current techniques of variable selection will be explicated. You will learn the use of Incremental-Response-Modeling to rate the impact of additional marketing actions. In addition you will learn how to use SAS Enterprise Miner for the analysis of Time Data and Survival Data Mining. In addition you will learn how to use SAS Enterprise Miner for the analysis of Time Series Data and for Survival Data Mining.

Who should attend

This course is for all Data Analysts and Forecaster who want to enhance their knowledge about advanced modeling techniqes with SAS Enterprise Miner.

Formats available	Standard duration
Classroom:	3 days

To get the most out of this course you should have some knowledge and experience with SAS Enterprise Miner. You can gain this knowlegde in the course Applied Analytics Using SAS Enterprise Miner

This course addresses SAS Enterprise Miner software.

Advanced Techniques of Prodictive Modeling for Classification and Regression

• Support vector machines, Gradient boosting, Rule induction (Modeling of seldom Events)
• Advanced Methodes of Variable Selection (LARS/LASSO, Variables Clustering, Principal Component Analysis PCA, Partial Least Squares Regression)
• Incremental Response-Modeling (Net Lifting)
• Import and Use of external models

Data Mining for Time Data

• Preparation of Time Data
• Analysis of similarity of different Time Series
• Time Series Models with sliding average

Introduction in Survival Data Mining

Additional hints to increase your efficiency with SAS Enterprise Miner