A Scikit-learn style wrapper for H2O estimators.
Project description
Wetsuit
A Scikit-Learn wrapper for H2O Estimators.
Why Wetsuit
While H2O Estimators have the .fit()
and .predict()
methods of the Scikit-Learn API, they don't always
function as expected, especially with Pipeline
objects. This package contains two estimators and a
single transformer to remedy.
For example. the H2OEstimator.fit()
method expects two H2OFrame
objects, vice pandas DataFrame
or
numpy NDArray
objects. Wetsuit provides two options for handling this behavior:
WetsuitRegressor
andWetsuitClassifier
classes that wrapH2OEstimator
objects and handle type conversion automatically, within the.fit()
and.predict()
methods.H2oFrameTransformer
class that converts bothDataFrame
andNDArray
objects toH2OFrame
objects via.fit_transform()
, and an.inverse_transform()
method to convert back.
Install
Create a virtual environment with Python >= 3.9 and install from git:
pip install git+https://github.com/chris-santiago/wetsuit.git
Use
Documentation
Documentation hosted on Github Pages: https://chris-santiago.github.io/wetsuit/
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.