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Predictive Modeling for Continuous Targets Using IBM SPSS Modeler (v18.1.1) SPVC

Course content updated by LearnQuest
Price
525 - 815 USD
8 Hours
0E0V8GS
Self-Paced Training
IBM Business Partner
Limited Time Offer
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  • Learn on Demand
    Location: Virtual
    Language: English
    Delivered by: LearnQuest
    Price: 525 USD
  • Date: 22-Aug-2022
    Time: 9AM - 5PM US Eastern
    Location: Virtual
    Language: English
    Delivered by: LearnQuest
    Price: 815 USD
  • Date: 19-Sep-2022
    Time: 9AM - 5PM US Eastern
    Location: Virtual
    Language: English
    Delivered by: LearnQuest
    Price: 815 USD
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Course Description

Overview

Contains PDF course guide, as well as a lab environment where students can work through demonstrations and exercises at their own pace.

This course 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. Students are introduced to machine learning models, such as Neural Networks. Business use case examples include: predicting the length of subscription for newspapers, telecommunication, and job length, as well as predicting insurance claim amounts.

If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course. http://www.ibm.com/training/terms

Objectives

1: Introduction to predictive models for continuous targets • List three modeling objectives • List two business questions that involve predicting continuous targets • Explain the concept of field measurement level and its implications for selecting a modeling technique • List three types of models to predict continuous targets • Determine the classification model to use  

2: Building decision trees interactively • Explain how CHAID grows a tree • Explain how C&R Tree grows a tree • Build CHAID and C&R Tree models interactively • Evaluate models for continuous targets • Use the model nugget to score records

 

3: Building decision trees directly • Customize two options in the CHAID node • Customize two options in the C&R Tree node • List one difference between CHAID and C&R Tree  

4. Using traditional statistical models • Explain key concepts for Linear • Customize options in the Linear node • Explain key concepts for Cox • Customize options in the Cox node  

5: Using machine learning models • Explain key concepts for Neural Net • Customize one option in the Neural Net node

Audience

IBM SPSS Modeler Analysts who have completed the Introduction to IBM SPSS Modeler and Data Mining course who want to become familiar with the modeling techniques available in IBM SPSS Modeler to predict a continuous target.

Prerequisites

     • 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 a basic   knowledge of modeling. • Prior completion of Introduction to IBM SPSS Modeler and Data Science (v18.1) is recommended.

Topics

1: Introduction to predicting continuous targets
• List three modeling objectives
• List two business questions that involve predicting continuous targets
• Explain the concept of field measurement level and its implications for selecting a modeling technique
• List three types of models to predict continuous targets
• Determine the classification model to use

2: Building decision trees interactively
• Explain how CHAID grows a tree
• Explain how C&R Tree grows a tree
• Build CHAID and C&R Tree models interactively
• Evaluate models for continuous targets
• Use the model nugget to score records

3: Building your tree directly
• Explain the difference between CHAID and Exhaustive CHAID
• Explain boosting and bagging
• Identify how C&R Tree prunes decision trees
• List two differences between CHAID and C&R Tree

4: Using traditional statistical models
• Explain key concepts for Linear
• Customize options in the Linear node
• Explain key concepts for Cox
• Customize options in the Cox node

5: Using machine learning models
• Explain key concepts for Neural Net
• Customize one option in the Neural Net node

 

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Self-Paced Training Info

Learn at your own pace with anytime, anywhere training

  • Same in-demand topics as instructor-led public and private classes.
  • Standalone learning or supplemental reinforcement.
  • e-Learning content varies by course and technology.
  • View the Self-Paced version of this outline and what is included in the SPVC course.
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Self-Paced Training Terms & Conditions

THIS IS A SELF-PACED VIRTUAL CLASS. AFTER YOU REGISTER, YOU HAVE 30 DAYS TO COMPLETE THE COURSE.

This is a Self-Paced virtual class; it is intended for students who do not need the support of a classroom instructor. If you feel you would better benefit from having access to a Subject Matter Expert, please enroll in the Instructor-Led version instead. Minimal technical support is provided to address issues with accessing the platform or problems within the lab environment.

Before you enroll, review the system requirements to ensure that your system meets the minimum requirements for this course. AFTER YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT. You are billed for the course when you submit the enrollment form. Self-Paced Virtual Classes are non-refundable. Once you purchase a Self-Paced Virtual Class, you will be charged the full price.

After you receive confirmation that you are enrolled, you will be sent further instructions to access your course material and remote labs. A confirmation email will contain your online link, your ID and password, and additional instructions for starting the course.

You can start the course at any time within 12 months of enrolling for the course. After you register/start the course, you have 30 days to complete your course. Within this 30 days, the self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day.

If the course requires a remote lab system, the lab system access is allocated on a first-come, first-served basis. When you are not using the elab system, ensure that you suspend your elab to maximize your hours available to use the elab system.

Click the Skytap Connectivity Test button to ensure this computer's hardware, software and internet connection works with the SPVC Lab Environment.

Click the Skytap Connectivity Documentation button to read about the hardware, software and internet connection requirements.

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