Install

EvalML is available for Python 3.6+. It can be installed by running the following command:

pip install evalml

Core vs Optional Dependencies

EvalML includes several optional dependencies. The xgboost and catboost packages support pipelines built around those modeling libraries. The plotly and ipywidgets packages support plotting functionality in automl searches. These dependencies are recommended, and are included with EvalML by default but are not required in order to install and use EvalML.

EvalML’s core dependencies are listed in core-requirements.txt in the source code, and optional requirements are isted in requirements.txt.

To install EvalML with only the core required dependencies, download the EvalML source from pypi to access the requirements files. Then run the following:

pip install evalml --no-dependencies
pip install -r core-requirements.txt

Windows

The XGBoost library may not be pip-installable in some Windows environments. If you are encountering installation issues, please try installing XGBoost from Github before installing EvalML.

EvalML is an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective functions. Start