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
- Actively incorporates innovative experimental interpretability techniques and allows for further expansion by researchers and data scientists
- Applies optimizations to make it possible to run interpretability techniques on real-world datasets at scale
- 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
- Provides interactive and exploratory visualizations to empower data scientists to gain meaningful insight into their data
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:
#inner { margin-left:50px; margin-right:-50px; }1. Set up Environment
a. Install Anaconda with Python >= 3.7Miniconda 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 repositorygit 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:lightgbm installation if desired:conda install --yes --quiet pytorch torchvision captum cpuonly -c pytorch
pip install --upgrade lightgbm
On Linux:
Pytorch installation if desired:conda install --yes --quiet pytorch torchvision captum cpuonly -c pytorch
lightgbm installation if desired:
pip install --upgrade lightgbm
On MacOS:
Pytorch installation if desired:
conda install --yes --quiet pytorch torchvision captum -c pytorch
lightgbm installation if desired (requires Homebrew):
If installing the package generally gives an error about the `certifi` package, run this first:brew install libomp
pip install --upgrade lightgbm
pip install --upgrade certifi --ignore-installed
pip install interpret-community
4. Set up and run Jupyter Notebook server
Install and run Jupyter Notebookif needed:
pip install jupyter
then:
jupyter notebook