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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 prior data mining background is required.
Target Audience
- Data analysts.
- Anyone eager to learn about SPSS Modeler.
14 Hours
Testimonials (2)
Doing Exercise
Joe Pang - Lands Department, Hong Kong
Course - QGIS for Geographic Information System
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
