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
Testimonials (5)
practical knowledge of the trainer
Waldek - Polska Spółka Gazownictwa sp. z o.o.
Machine Translated
The training is very interesting and can be useful on our future projects and the trainer is always active on answering our questions and helping us when we are having issues on our end.
Charles Kevin Regaliza - Thakral One Inc.
Course - Introduction to Drools 7 for Developers
I loved that he was able to see our machines to help us when we got stuck.
Megan Burns - Sandia National Labs
Course - Drools 7 and DSL for Business Analysts
I liked the positive and optimistic attitude. Gives good answers to questions.
Emil Krabbe Nielsen
Course - Introduction to Drools 6 for Developers
I really enjoyed the good atmosphere.