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

1.225,00€

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.

SKU: 11. Category: SPSS
  • Description

Description

At SIXE we have been providing official IBM training around the world for over 12 years. Get the best training from our specialists in Europe. We have important discounts and offers for two or more students.

Course details

IBM course code: 0A0V8GCategory: IBM SPSS Modeler / IBM SPSS Modeler
Delivery: Online & on-site**Course length in days: 1

Target 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.

Desired 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 (v18.1.1) is recommended.

Instructors

The great majority of the IBM courses we offer are taught directly by our engineers. This is the only way we can guarantee the highest quality. We complement all the training with our own materials and laboratories, based on our experience during the deployments, migrations and courses that we have carried out during all these years.

Added value

Our courses are deeply role oriented. To give an example, the needs for technology mastery are different for developer teams and for the people in charge of deploying and managing the underlying infrastructure. The level of previous experience is also important and we take it very seriously. That is why beyond (boring) commands and tasks, we focus on solving the problems that arise in the day to day of each team. Providing them with the knowledge, competencies and skills required for each project. In addition, our documentation is based on the latest version of each product.

Agenda and course syllabus

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

Do you need to adapt this syllabus to your needs? Are you interested in other courses?  Ask us without obligation.

Locations for on-site delivery

  • Austria: Vienna
  • Belgium: Brussels, Ghent
  • Denmark: Cophenhagen
  • Estonia: Tallinn
  • Finland: Helsinki
  • France: Paris, Marseille, Lyon
  • Germany: Berlin, Munich, Cologne, Hamburg
  • Greece: Athens, Thessaloniki
  • Italy: Rome
  • Louxemburg: Louxembourg (city)
  • Netherlands: Amsterdam
  • Norway: Oslo
  • Portugal: Lisbon, Braga, Porto, Coimbra
  • Slovakia: Bratislava
  • Slovenia: Bratislava
  • Spain: Madrid, Sevilla, Valencia, Barcelona, Bilbao, Málaga
  • Sweden: Stockholm
  • Turkey: Ankara
  • United Kingdom: London

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