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

Course Outline

1: Introduction to predictive models for categorical targetsIdentify three modeling objectivesExplain the concept of field measurement level and its implications for selecting a modeling techniqueList three types of models to predict categorical targets2: Building decision trees interactively with CHAIDExplain how CHAID grows decision treesBuild a customized model with CHAIDEvaluate a model by means of accuracy, risk, response and gainUse the model nugget to score records3: Building decision trees interactively with C&R Tree and QuestExplain how C&R Tree grows a treeExplain how Quest grows a treeBuild a customized model using C&R Tree and QuestList two differences between CHAID, C&R Tree, and Quest4: Building decision trees directlyCustomize two options in the CHAID nodeCustomize two options in the C&R Tree nodeCustomize two options in the Quest nodeCustomize two options in the C5.0 nodeUse the Analysis node and Evaluation node to evaluate and compare modelsList two differences between CHAID, C&R Tree, Quest, and C5.05: Using traditional statistical modelsExplain key concepts for DiscriminantCustomize one option in the Discriminant nodeExplain key concepts for LogisticCustomize one option in the Logistic node6: Using machine learning modelsExplain key concepts for Neural NetCustomize 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