Skip to main content

No project description provided

Project description

Microsoft Azure Machine Learning Explain Model API for Python

This package has been tested with Python 2.7 and 3.6.

The SDK is released with backwards compatibility guarantees.

Machine learning (ML) explain model package is used to interpret black box ML models.

  • The TabularExplainer can be used to give local and global feature importances

  • The best explainer is automatically chosen for the user based on the model

  • Local feature importances are for each evaluation row

  • Global feature importances summarize the most importance features at the model-level

  • The API supports both dense (numpy or pandas) and sparse (scipy) datasets

  • For more advanced users, individual explainers can be used

  • The KernelExplainer and MimicExplainer are for BlackBox models

  • The MimicExplainer is faster but less accurate than the KernelExplainer

  • The TreeExplainer is for tree-based models

  • The DeepExplainer is for DNN tensorflow or pytorch models

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

azureml_explain_model-1.0.83-py3-none-any.whl (22.8 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page