This course presents advanced techniques to predict categorical and continuous targets. Before reviewing the modeling techniques, data preparation issues are addressed such as partitioning and detecting anomalies. Also, a method to reduce the number of fields to a number of core fields, referred to as components or factors, is presented. Advanced classification models, such as Decision List, Support Vector Machines and Bayes Net, are reviewed. Methods are presented to combine individual models into a single model in order to improve predictive power, including running and evaluating many models in a single run, both for categorical and continuous targets.
Who is it for?
This course is aimed at users of IBM SPSS Modeler responsible for building predictive models who want to leverage the full potential of classification models in IBM SPSS Modeler.
What should I have?
Our trainer is an experienced IBM-SPSS Statistics and DataMining Consultant
Refreshments and course notes included
1. Preparing Data for Modeling
2. Reducing Data with PCA/Factor
3. Using Decision List to Create Rulesets
4. Exploring advanced predictive models
5. Combining Models
6. Finding the Best Predictive Model
*Disclaimer: Kindly note the scheduled dates below are tentative and are therefore subject to change. Please, do register your interest as we are taking provisional bookings.