Course Outline

Introduction

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

Understanding Data

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

Data Preparation

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

Modeling

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

Evaluation and Deployment

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

Troubleshooting

Summary and Next Steps

Requirements

  • No data mining background needed

Audience

  • Data analysts
  • Anyone who wants to learn about SPSS Modeler
  14 Hours
 

Testimonials

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