Loading...

IBM SPSS Modeler

Home / IBM Training Initiative  / IBM SPSS Modeler
* Courses listed below can also be customized based on user demandDon't see a course that you are looking for?
Click Here to Request It.

0A0U7G – Predictive Modeling for Categorical Targets Using IBM SPSS Modeler

Predictive Modeling for Categorical Targets Using IBM SPSS Modeler (v18) (formerly Classifying Customers Using IBM SPSS Modeler) focuses on analytical models to predict a categorical field (churn, fraud, response to a mailing, pass/fail exams, machine break-down, and so forth). Students will be introduced to decision trees such as CHAID and C&R Tree, traditional statistical models such as Logistic Regression, and machine learning models such as Neural Networks. The student will learn about important options in dialog boxes, how to interpret the results, and explain the major differences between the models.

  • In-class
  • Instructor Led Online
  • Self-Paced Virtual Classroom
Register for self-paced course

0A0V5G – Predicting Continuous Targets Using IBM SPSS Modeler

Predicting Continuous Targets Using IBM SPSS Modeler (v16) is an intermediate level course that provides an overview of how to use IBM SPSS Modeler to predict a target field that describes numeric values. Students will be exposed to rule induction models such as CHAID and C&R Tree. They will also be introduced to traditional statistical models such as Linear Regression. Machine learning models will also be presented. Business use case examples include: predicting the length of subscription (for newspapers, telecommunication, job length, and so forth) and predicting claim amount (insurance).

  • In-class
  • Instructor Led Online
  • Self-Paced Virtual Classroom
Register for self-paced course

0A0V7G – Predictive Modeling for Continuous Targets Using IBM SPSS Modeler

This course (formerly Predicting Continuous Targets Using IBM SPSS Modeler (v16)) provides an overview of how to use IBM SPSS Modeler to predict a target field that describes numeric values. Students will be exposed to rule induction models such as CHAID and C&R Tree. They will also be introduced to traditional statistical models such as Linear Regression. Machine learning models will also be presented. Business use case examples include: predicting the length of subscription (for newspapers, telecommunication, job length, and so forth) and predicting claim amount (insurance).

  • In-class
  • Instructor Led Online
  • Self-Paced Virtual Classroom
Register for self-paced course

0A105G – Introduction to IBM SPSS Text Analytics for IBM SPSS Modeler

Introduction to IBM SPSS Text Analytics for IBM SPSS Modeler (V16) teaches users how to analyze text data using IBM SPSS Modeler Text Analytics. Students will see the complete set of steps involved in working with text data, from reading the text data to creating the final categories for additional analysis. After the final model has been created, there is an example of how to apply the model to perform Churn analysis. Topics include how to automatically and manually create and modify categories, how to edit synonym, type, and exclude dictionaries, and how to perform Text Link Analysis and Cluster Analysis with text data. Also included are examples of how to create resource templates and Text Analysis packages to share work with other projects and other users.

  • In-class
  • Instructor Led Online
  • Self-Paced Virtual Classroom
Register for self-paced course

0E032G – Predictive Modeling with IBM SPSS Modeler SPVC

Predictive Modeling with IBM SPSS Modeler demonstrates how to develop models to predict categorical and continuous outcomes, using such techniques as neural networks, decision trees, logistic regression, support vector machines, and Bayesian network models. Use of the binary classifier and numeric predictor nodes to automate model selection is included. Feature selection and detection of outliers are discussed. Expert options for each modeling node are reviewed in detail and advice is provided on when and how to use each model. Students will also learn how to combine two or more models to improve prediction.

 

Please note: This course is only available in the self-paced format. The in-class version of this training has been retired by IBM, and has been replaced by 0A0U5 – Classifying Customers Using IBM SPSS Modeler.

 

  • Self-Paced Virtual Classroom
Register for self-paced course