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 (7)
practical knowledge of the trainer
Waldek - Polska Spółka Gazownictwa sp. z o.o.
Course - IBM ODM Decision Management
Machine Translated
I really enjoyed the good atmosphere.
Martin Jesterschawek
Course - Business Rule Management (BRMS) with Drools
I liked the positive and optimistic attitude. Gives good answers to questions.
Emil Krabbe Nielsen
Course - Introduction to Drools 6 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
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 appreciate the fact that they address my suggestion before to share the presentation with manual before the training. Very helpful on my part. Also, the individual activity, I liked it, our trainer were able to see how we interpret each case scenarios.
Kim Justine Ferriol - Thakral One, Inc.
Course - jBPM and Drools
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.