counterfactual-xai 0.0.2

Remove uncertainty from your machine learning models

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Counterfactuals: Take the uncertainty out of your machine learning models

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[Documentation](/docs) | [Examples](/examples) | [Showcase](/docs/showcase.md)

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Counterfactuals is a Python library for machine learning that enables you to better understand your models. We combine several techniques to provide a comprehensive understanding of your model’s predictions. With those insights you are able to eliminate uncertainties and make better decisions.

## Features

### CLUE: A Method for Explaining Uncertainty Estimates

CLUE is a method for explaining uncertainty estimates of machine learning models. It is based on the idea of counterfactuals and provides a comprehensive understanding of the model’s predictions.

Model Paper: [CLUE: A Method for Explaining Uncertainty Estimates](https://arxiv.org/abs/2006.06848)

## Installation

The current recommended way to install tinygrad is from source.

### From source

`sh git clone https://github.com/lsch0lz/counterfactuals.git cd counterfactuals python3 -m pip install -e . `

### Direct (master)

`sh python3 -m pip install git+https://github.com/lsch0lz/counterfactuals.git `

## Documentation

Documentation along with a quick start guide can be found in the [docs/](/docs) directory.