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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 data mining background needed
Audience
- Data analysts
- Anyone who wants to learn about SPSS Modeler
14 Hours
Testimonials (5)
how the trainor shows his knowledge in the subject he's teachign
john ernesto ii fernandez - Philippine AXA Life Insurance Corporation
Course - Data Vault: Building a Scalable Data Warehouse
The content, as I found it very interesting and think it would help me in my final year at University.
Krishan - NBrown Group
Course - From Data to Decision with Big Data and Predictive Analytics
I enjoyed the good real world examples, reviews of existing reports.
Ronald Parrish
Course - Data Visualization
Very tailored to needs.
Yashan Wang
Course - Data Mining with R
The trainer was so knowledgeable and included areas I was interested in.