h2oparsnip

h2oparsnip provides a set of wrappers to bind h2o algorthms with the 'parsnip' package.

This package is early in development. Currently the following h2o algorithms are implemented:

• h2o.deeplearning engine added to parsnip::mlp model specification
• h2o.gbm engine added to parsnip::boost_tree model specification
• h2o.randomForest engine added to parsnip::rand_forest model specification
• h2o.glm engine added to multinom_reg, logistic_reg and linear_reg model specifications
• h2o.naiveBayes engine added to naive_Bayes specification (requires the discrim package)
• a new model, automl

Installation

The package is not yet on CRAN and can be installed with:

devtools::install_github("stevenpawley/h2oparsnip")

Needed

Add multi_predict method for h2o.gbm using h2o.staged_predict_proba