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

IBM0A0V8G

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.

Argomenti

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

Obiettivi

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
  1. 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

Prezzo di listino

700,00 EUR + IVA per partecipante

Durata

  • 8 ore
  • 1 giorno

Prerequisiti

  • 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.

Prossime edizioni

Erogabile on-line e on-site

Tutti i nostri corsi sono erogabili anche in modalitĂ  on-line (con formazione a distanza), oppure on-site, sempre personalizzati secondo le esigenze.

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