Predictive Modeling Using Logistic Regression

  • Modelers, analysts and statisticians who need to build predictive models, particularly models from the banking, financial services, direct marketing, insurance and telecommunications industries

Prerequisite
Please contact us for information about prerequisites.

Expected Duration
2 day

Description

In this course, you will learn about predictive modeling using SAS/STAT software with emphasis on the LOGISTIC procedure. You will also learn about selecting variables and interactions, recoding categorical variables based on the smooth weight of evidence, assessing models, treating missing values, and using efficiency techniques for massive data sets.

Certification:

SAS Statistical Business Analysis Using SAS 9: Regression and Modeling

Objective

1. Predictive Modeling

  • Business applications
  • Analytical challenges

2. Fitting the Model

  • Parameter estimation
  • Adjustments for oversampling

3. Preparing the Input Variables

  • Missing values
  • Categorical inputs
  • Variable clustering
  • Variable screening
  • Subset selection

4. Classifier Performance

  • ROC curves and Lift charts
  • Optimal cutoffs
  • K-S statistic
  • c statistic
  • Profit
  • Evaluating a series of models

SUBSCRIPTION COST


$1,600.00

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