Abstract
This document is about Who Has What? Predictive Modeling Using Customer Billing Data
Table of Contents
- Table of Contents
- Energy Insights Opinion
- In This Report
- Situation Overview
- Applications
- Method Specifics
- Predictive Modeling Techniques
- Logistic Regression
- Discriminant Analysis
- CHAID
- Table: Summary of Predictive Modeling Techniques
- Accuracy and Error Rates
- Figure: Type I and Type II Errors
- General Comments About Modeling
- Predictive Modeling Techniques
- Case Study 1: San Diego Gas & Electric and Central AC
- Background and Setup
- Logistic Regression Results
- Table: Summary of Logistic Regression Models Predicting the Presence of Central AC: SDG&E Case Study
- Figure: Predicted Error Rates and Accuracy for Central AC Using Logistic Regression: SDG&E Case Study
- Table: Comparison of Logistic Regression Results with Classification Probabilities of 0.5 and 0.4: SDG&E Case Study
- Discriminant Analysis Results
- Table: Summary of Discriminant Analysis Models Predicting the Presence of Central AC: SDG&E Case Study
- CHAID Results
- Figure: Partial CHAID Tree for Central AC Model: SDG&E Case Study
- Comparison of Methods for Central AC Data
- Table: Comparison of Logistic Regression, Discriminant Analysis, and CHAID Models Predicting the Presence of Central AC: SDG&E Case Study
- Follow-Up Real-World Application
- Case Study 2: Alliant Energy and Electric Heat
- Background and Setup
- Defining the Criterion Variable
- Overall Modeling Approach
- Logistic Regression Results
- Table: Logistic Regression and Discriminant Analysis Models Predicting the Presence of Electric Heat: Alliant Energy Case Study
- Figure: Predicted Error Rates and Accuracy for Electric Heat Using Logistic Regression: Alliant Energy Case Study
- Discriminant Analysis Results
- CHAID Results
- Figure: CHAID Tree for Electric Heat Model: Alliant Energy Case Study
- Comparison of Methods for Electric Heat Data
- Background and Setup
- Lessons Learned
- Future Outlook
- Essential Guidance
- Actions to Consider
- Learn More
- Related Research
- Synopsis







