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Course Outline
Introduction
- Why extract rules from data?
Overview of Sklearn Modules (Decision Tree/Random Forrest)
Installing and Configuring skope-rules
Case Study: Detecting Credit Default Rates
Importing Data
Using SkopeRules for Imbalanced Classification
Training the SkopeRules Classifier
Extracting the Rules
Fusing the Rules
Fitting Classification and Regression Trees to Sub-samples
Selecting Higher Precision Rules
Testing Higher Precision Rules
Summary and Conclusion
Requirements
- Python programming experience
- Knowledge of machine learning algorithms
Audience
- Developers
14 Hours