1. Binary Classification Class
Project Flow Overview

2. Binary Classification Project Flow
Step 1
Variable Selection
Primary Issue: Little knowledge of content
Step 2
Variable Cleansing
Primary Issue: Mixed Variables
Step 3
Variable Reduction
Primary Issue: Multicollinearity
STAT4330/8330 PRIESTLEY

3. Binary Classification Project Flow
Step 4
Discretization Process One (equal width categories)
Primary Issue: Determining user defined cut points for ordinal values
Step 5
Discretization Process Two (equal frequency categories)
Primary Issue: Understanding the output from SAS
Step 6
Model Development
Primary Issue: Interpretation of beta coefficients
STAT4330/8330 PRIESTLEY

4. Binary Classification Project Flow
Step 7
Model Evaluation
Primary Issue: Interpretation of ROC, Profit Function, Gains Chart, Classification Table
Step 8
Behavior Analysis/Cluster Analysis
Primary Issue: Method to determine behavior of good/bad
Step 9
Report and Presentation
STAT4330/8330 PRIESTLEY