Introduction to Predictive Analytics with IBM SPSS Modeler

This three day course provides an overview of data mining and the fundamentals of using IBM SPSS Modeler. The principles and practice of predictive modelling are illustrated using the CRISP-DM methodology.

• Introduction to Data Mining
• The Basics of Using Modeler
• Reading Data Files
• Data Understanding
• Outliers and Anomalous Data
• Introduction to Data Manipulation
• Variable Relationships, Overview of Modelling techniques.
• Looking for Relationships in Data
• Combining Data Files
• Aggregating Data
• Selecting, Sampling and Partitioning Records
• Modelling Techniques in Modeler
• Automating models & tips and tricks for Modelling
• Rule Induction
• Automating Models for Binary Outcomes
• Automating Models for Numeric Outcomes
• Model Understanding
• Comparing and Combining Models
• Deploying and Using Models

Course attendees will receive sample data files and step-by-step exercises that can be completed following the course.

Best for: Those who are new to Modeler or have used it in the past, and would like a complete overview that includes data access, preparation, examination, modelling, model evaluation and deployment.