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 definitely backfilled some of the gaps in my knowledge left by reading the OptaPlanner userguide. It gave me a good broad understanding of how to approach using OptaPlanner in our projects going forward.
Terry Strachan - Exel Computer Systems plc
Course - OptaPlanner in Practice
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.