EAI Programs

This repository contains the Python programs that I worked in Explainable AI class.

Index

• Logistic Regression Programs
  • Iris dataset
  • Red Wine Dataset
  • NYC Taxi Fare Prediction
• LIME (Local Interpretable Model-Agnostic Explanations)
  • Red Wine Dataset
• 2D Projection
  • Iris Dataset

Prerequisites

Python and packages in requirements.txt file installed.

Note

You can install all the packages in the file using the command pip install -r requirements.txt.

Working with Conda

If you are using conda to manage your environments, you can create a new environment for this repository with the command conda create -n eai and activate it with the command conda activate eai.

Tip

For faster environment solving in Conda, I would suggesting using the libmamba solver. You can set it as the default solver using the command conda config --set solver libmamba.

Then, you can install all the required packages using the command conda install --file requirements.txt.

Container Image

Alternatively, you can use the container image I created with all the packages preinstalled.

You can install it in Distrobox with the command distrobox create -i ghcr.io/kbdharun/eai-image:latest -n eai and use it with the command distrobox enter eai.

Additionally, you can verify the authenticity of the container image using cosign (download the cosign.pub file from here and execute the following command):

cosign verify --key cosign.pub ghcr.io/kbdharun/eai-image:latest