Classes of Models in IBM SPSS Modeler

IBM SPSS Modeler is an extensive predictive analytics platform designed to bring predictive intelligence to decisions made by individuals, groups, systems, and the enterprise. IBM SPSS Modeler has an easy-to-use drag-and-drop user interface with a complete set of tools for accessing data, data examination, preparation, modelling, evaluation, and deployment.  

IBM SPSS Modeler users have a complete toolset to build predictive models from start to finish. Modeler uses node-based, visual programming. Users pick nodes from palettes and place them on the stream canvas. Once nodes have been placed on the stream canvas and edited, they can be linked to form a stream. A stream represents a flow of data through several operations (nodes) to a destination that can be in the form of output (either text or chart), a model, or the export of data to another format (e.g., a database).  

The SPSS team at Version 1 provides extensive Modeler training, offering both express and longer courses. Training can also be customised for individual users and groups.  

IBM SPSS Modeler is a complete data science platform with classes of models that provide solutions for data types and business questions. The classes of models are built into the user interface, which makes finding the type of model needed easy. This two-hour express course covers the classes of models in IBM SPSS Modeler. Predictive, association and cluster models will be reviewed along with examples of each and practical applications.

This course will cover the following topics:

• Review of classes of models
• Predictive Models with demo
• Clustering Models with demo
• Association Models with demo

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

Best for: Analysts and data scientists who want to understand classes of models and the various modelling options in IBM SPSS Modeler.