Live Chat
Monday - Friday 8am - 6pm EST Chat Now
Contact Us
Monday - Friday 8am - 8pm EST 1-866-716-6688 Other Contact Options

Cart () Loading...

    • Quantity:
    • Delivery:
    • Dates:
    • Location:


Advanced Predictive Modeling Using IBM SPSS Modeler (v18)

Learn advanced techniques to predict categorical and continuous targets using IBM SPSS Modeler.

GK# 6015 Vendor# 0A037G

$360 - $995 USD

Enroll Request Group Training

Course Overview


In this course, you will learn about advanced techniques used for predicting 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.


  • Delivery Format:
  • Date:
  • Location:
  • Access Period:


What You'll Learn

  • Preparing data for modeling
  • Reducing data with PCA/Factor
  • Using decision list to create rulesets
  • Exploring advanced predictive models
  • Combining models
  • Finding the best predictive model


Viewing outline for:

Classroom Live Outline

1. Preparing Data for Modeling

  • Address general data quality issues
  • Handle anomalies
  • Select important predictors
  • Partition the data to better evaluate models
  • Balance the data to build better models

2. Reducing Data with PCA/Factor

  • Explain the basic ideas behind PCA/Factor
  • Customize two options in the PCA/Factor node

3. Using Decision List to Create Rulesets

  • Explain how Decision List builds a ruleset
  • Use Decision List interactively
  • Create rulesets directly with Decision List

4. Exploring Advanced Predictive Models

  • Explain the basic ideas behind SVM
  • Customize two options in the SVM node
  • Explain the basic ideas behind Bayes Net
  • Customize two options in the SVM node

5. Combining Models

  • Use the Ensemble node to combine model predictions
  • Improve the model performance by meta-level modeling

6. Finding the Best Predictive Model

  • Find the best model for categorical targets with AutoClassifier
  • Find the best model for continuous targets with AutoNumeric


  • General computer literacy
  • Experience using IBM SPSS Modeler including familiarity with the Modeler environment, creating streams, reading data files, exploring data, setting the unit of analysis, combining datasets, deriving and reclassifying fields, and basic knowledge of modeling
  • Prior completion of Introduction to Predictive Models using IBM SPSS Modeler (v18) is recommended
  • Familiarity with basic modeling techniques

Who Should Attend

  • Data modelers
  • Data analysts
  • Data scientists
Training Exclusives

This course comes with the following benefits: 

  • Digital Courseware
  • 90 Days Bonus Access to IBM Hands-on Labs
  • 12 Months of Indexed Virtual Class Recordings
Learn More
Course Delivery

This course is available in the following formats:

Classroom Live

Receive face-to-face instruction at one of our training center locations.

Duration: 1 day

Virtual Classroom Live

Experience expert-led online training from the convenience of your home, office or anywhere with an internet connection.

Duration: 1 day


On-demand content enables you to train on your own schedule.

Request this course in a different delivery format.