Overview

Interpret-Community extends the Interpret repository and incorporates further community developed and experimental interpretability techniques and functionalities that are designed to enable interpretability for real world scenarios. Interpret-Community enables adding new experimental techniques (or functionalities) and performing comparative analysis to evaluate them.

Interpret-Community

  1. Actively incorporates innovative experimental interpretability techniques and allows for further expansion by researchers and data scientists

  2. Applies optimizations to make it possible to run interpretability techniques on real-world datasets at scale

  3. Provides improvements such as the capability to “reverse the feature engineering pipeline” to provide model insights in terms of the original raw features rather than engineered features

  4. Provides interactive and exploratory visualizations to empower data scientists to gain meaningful insight into their data

Getting Started

The package can be installed from pypi with:

pip install interpret-community

You can use Anaconda to simplify package and environment management.

To setup on your local machine:

1. Set up Environment a. Install Anaconda with Python >= 3.7
Miniconda is a quick way to get started.

b. Create conda environment named interp and install packages
conda create --name interp python=3.7 anaconda

Optional, additional reading:
conda cheat sheet jupyter nb_conda
On Linux and Windows: c. Activate conda environment
activate interp
On Mac: c. Activate conda environment
source activate interp
2. Clone the Interpret-Community repository Clone and cd into the repository
git clone https://github.com/interpretml/interpret-community
                
cd interpret-community
3. Install Python module, packages and necessary distributions
pip install interpret-community

If you intend to run repository tests:
pip install -r requirements.txt
On Windows: Pytorch installation if desired:
conda install --yes --quiet pytorch torchvision cpuonly -c pytorch
            
pip install captum
lightgbm installation if desired:
pip install --upgrade lightgbm
On Linux: Pytorch installation if desired:
conda install --yes --quiet pytorch torchvision cpuonly -c pytorch
            
pip install captum

lightgbm installation if desired:
pip install --upgrade lightgbm
On MacOS:
Pytorch installation if desired:
conda install --yes --quiet pytorch torchvision -c pytorch
            
pip install captum

lightgbm installation if desired (requires Homebrew):
brew install libomp
            
pip install --upgrade lightgbm
If installing the package generally gives an error about the `certifi` package, run this first:
pip install --upgrade certifi --ignore-installed
            
pip install interpret-community
4. Set up and run Jupyter Notebook server Install and run Jupyter Notebook if needed:
            
pip install jupyter
then:
            
jupyter notebook