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
 

Number of participants


Starts

Ends


Dates are subject to availability and take place between 09:30 and 16:30.
Open Training Courses require 5+ participants.

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