H2O AutoDoc Python Documentation¶
This document provides an overview of the H2O AutoDoc Python package’s usages and API.
Requirements
Python 3.6 or 3.7
H2O AutoDoc Python client
Have Questions?
If you have questions about using H2O AutoDoc, post them on the H2O.ai Community Slack workspace in the #autodoc channel. If you have not signed up for the H2O.ai Community Slack workspace, you can do so here: https://www.h2o.ai/community/.
H2O AutoDoc Python Module
- Introduction to H2O AutoDoc
- Installing H2O AutoDoc
- Creating & Configuring H2O AutoDoc
- Building an H2O Model
- Generate a Default H2O AutoDoc
- Push Generated AutoDoc to S3 Bucket
- Push Generated AutoDoc to Github Repository
- Set the H2O AutoDoc File Type
- Model Interpretation Dataset
- Partial Dependence Features
- Specify ICE Records
- Enable/Disable Shapley Values
- Provide Additional Testsets
- Provide Alternative Models
- H2O AutoDoc API Docs
Steam
- Using H2O AutoDoc with Steam
- Introduction
- Configure H2O AutoDoc
- Connecting to H2O-3 Cluster
- Connecting to Sparkling Water Cluster
- Build H2O Model on connected cluster (H2O-3 / Sparkling Water)
- Generate and Download a Default H2O AutoDoc
- Push Generated AutoDoc to S3 Bucket
- Push Generated AutoDoc to Github Repository
- Set the H2O AutoDoc File Type
- Model Interpretation Dataset
- Partial Dependence Features
- Specify ICE Records
- Enable/Disable Shapley Values
- Saving AutoDoc to HDFS