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Course Outline

Introduction

  • Overview of advanced analytics and data mining
  • Overview of CRISP-DM
  • Understanding the Modeler user interface
  • Understanding the mechanics of building streams

Understanding Data

  • Reading data into Modeler
  • Measurement levels and field roles
  • Using the data audit node

Data Preparation

  • Selecting cases
  • Reclassifying categorical values
  • Using the append node and merge node
  • Deriving fields

Modelling

  • Overview of modelling
  • Using a partition node
  • Building a CHAID model
  • Model assessment

Evaluation and Deployment

  • Using the analysis and evaluation node
  • Scoring new data and exporting results
  • Using the flat file node

Troubleshooting

Summary and Next Steps

Requirements

  • No prior data mining experience required

Audience

  • Data analysts
  • Anyone interested in learning about SPSS Modeler
 14 Hours

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Provisional Upcoming Courses (Require 5+ participants)

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