Schulung - IBM 0A0U8G - Predictive Modeling for Categorical Targets Using IBM SPSS Modeler (v18.1.1)

Course Outline

1: Introduction to predictive models for categorical targets
Identify three modeling objectives
Explain the concept of field measurement level and its implications for selecting a modeling technique
List three types of models to predict categorical targets

2: Building decision trees interactively with CHAID
Explain how CHAID grows decision trees
Build a customized model with CHAID
Evaluate a model by means of accuracy, risk, response and gain
Use the model nugget to score records

3: Building decision trees interactively with C&R Tree and Quest
Explain how C&R Tree grows a tree
Explain how Quest grows a tree
Build a customized model using C&R Tree and Quest
List two differences between CHAID, C&R Tree, and Quest

4: Building decision trees directly
Customize two options in the CHAID node
Customize two options in the C&R Tree node
Customize two options in the Quest node
Customize two options in the C5.0 node
Use the Analysis node and Evaluation node to evaluate and compare models
List two differences between CHAID, C&R Tree, Quest, and C5.0

5: Using traditional statistical models
Explain key concepts for Discriminant
Customize one option in the Discriminant node
Explain key concepts for Logistic
Customize one option in the Logistic node

6: Using machine learning models
Explain key concepts for Neural Net
Customize one option in the Neural Net node

Objective

1: Introduction to predictive models for categorical targets 
Identify three modeling objectives 
Explain the concept of field measurement level and its implications for selecting a modeling technique 
List three types of models to predict categorical targets 
 

2: Building decision trees interactively with CHAID 
Explain how CHAID grows decision trees 
Build a customized model with CHAID 
Evaluate a model by means of accuracy, risk, response and gain 
Use the model nugget to score records 
 

3: Building decision trees interactively with C&R Tree and Quest 
Explain how C&R Tree grows a tree 
Explain how Quest grows a tree 
Build a customized model using C&R Tree and Quest 
List two differences between CHAID, C&R Tree, and Quest

4: Building decision trees directly 
Customize two options in the CHAID node 
Customize two options in the C&R Tree node 
Customize two options in the Quest node 
Customize two options in the C5.0 node 
Use the Analysis node and Evaluation node to evaluate and compare models 
List two differences between CHAID, C&R Tree, Quest, and C5.0 
 

5: Using traditional statistical models 
Explain key concepts for Discriminant 
Customize one option in the Discriminant node 
Explain key concepts for Logistic 
Customize one option in the Logistic node 
 

6: Using machine learning models 
Explain key concepts for Neural Net 
Customize one option in the Neural Net node