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Course Outline
Introduction
- Overview of advanced analytics and data mining.
- Overview of the CRISP-DM methodology.
- Understanding the Modeler user interface.
- Grasping the mechanics of building data streams.
Understanding Data
- Importing data into Modeler.
- Measurement levels and field roles.
- Utilizing the data audit node.
Data Preparation
- Selecting cases.
- Reclassifying categorical values.
- Using the append and merge nodes.
- Deriving new fields.
Modeling
- Overview of modeling techniques.
- Using the partition node.
- Building a CHAID model.
- Model assessment.
Evaluation and Deployment
- Using the analysis and evaluation nodes.
- Scoring new data and exporting results.
- Utilizing the flat file node.
Troubleshooting
Summary and Next Steps
Requirements
- No prior experience in data mining is required.
Target Audience
- Data analysts.
- Anyone interested in learning 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.
