H2OGBM¶
H2O GBM
Input¶
It takes in a DataFrame as input
Type¶
transform
Class¶
fire.nodes.h2o.NodeH2OGbm
Fields¶
Details¶
Gradient Boosting Machine (for Regression and Classification) is a forward learning ensemble method. The guiding heuristic is that good predictive results can be obtained through increasingly refined approximations. H2O’s GBM sequentially builds regression trees on all the features of the dataset in a fully distributed way - each tree is built in parallel.
More details are available at : http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/gbm.html