evalml

EvalML is an AutoML library written in python.

Showing:

Popularity

Downloads/wk

0

GitHub Stars

386

Maintenance

Last Commit

1d ago

Contributors

30

Package

Dependencies

37

License

Categories

Readme

Featuretools

GitHub Actions Codecov.io PyPI PyPI Stats

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

Key Functionality

  • Automation - Makes machine learning easier. Avoid training and tuning models by hand. Includes data quality checks, cross-validation and more.
  • Data Checks - Catches and warns of problems with your data and problem setup before modeling.
  • End-to-end - Constructs and optimizes pipelines that include state-of-the-art preprocessing, feature engineering, feature selection, and a variety of modeling techniques.
  • Model Understanding - Provides tools to understand and introspect on models, to learn how they'll behave in your problem domain.
  • Domain-specific - Includes repository of domain-specific objective functions and an interface to define your own.

Install from PyPI

pip install evalml

Add-ons

Update checker

Receive automatic notifications of new EvalML releases

pip install evalml[update_checker]

Start

Load and split example data

import evalml
X, y = evalml.demos.load_breast_cancer()
X_train, X_test, y_train, y_test = evalml.preprocessing.split_data(X, y, problem_type='binary')

Run AutoML

from evalml.automl import AutoMLSearch
automl = AutoMLSearch(X_train=X_train, y_train=y_train, problem_type='binary')
automl.search()

View pipeline rankings

automl.rankings

Get best pipeline and predict on new data

pipeline = automl.best_pipeline
pipeline.predict(X_test)

Next Steps

Read more about EvalML on our documentation page:

Built at Alteryx Innovation Labs

Alteryx Innovation Labs

Rate & Review

Great Documentation0
Easy to Use0
Performant0
Highly Customizable0
Bleeding Edge0
Responsive Maintainers0
Poor Documentation0
Hard to Use0
Slow0
Buggy0
Abandoned0
Unwelcoming Community0
100