Python Library

This tutorial will guide you through how to get started with using the RIME Library in your Jupyter notebook.

Similar to the RIME Stress Testing Tutorial, we will be using the IEEE-CIS Fraud Detection dataset.

Since the RIME Library is directly accessible after installing our python package, please make sure to complete the steps in Installation first.

• Data and Model Setup

• AI Stress Tests

• RIME Adversarial
  • Overview
  • RIME Adversarial Attacks
  • Improving Adversarial Robustness with Attack Results
  • Highlighted Extra Features

• RIME Subset Performance
  • Overview
  • Using RIME Library to Analyze Model Performance
  • Improving Model Performance Results: Overweighting

• RIME Model Performance
  • Overview
  • Preprocessing
  • Active Learning