rf_autogrid: rf_autogrid

In andrewsommerlot/startml: Start doing machine learning with training optimization and ensembles of popular machine learning algorithms powered by scalable implementations in h2o

Description

rf_autogrid is a wrapper employing built-in settings to run grid search hyper parameter optimizations on the random forest algorithm.

Usage

rf_autogrid(train, valid, y, x, eval_metric = "AUTO", wd = getwd(),
  folds = NULL, rf_min_depth = 1, rf_max_depth = 7,
  rf_runtime_secs = 20, rf_stopping_rounds = 10,
  rf_stopping_tolerance = 1e-05, grid_strategy = "RandomDiscrete")

Arguments

train	H2O frame object containing labeled data for model training. No Default.
valid	H2O frame object containing labeled data for model validation. No Default.
y	Character object of length 1 identifying the column name of the target variable. No Default.
x	Character object of length 1 or more identifying the column name(s) of the input variables. No Default.
eval_metric	Character object defining evaluation metric for training. Defualt is "AUTO" and uses built-in H2O automatic choice for target data type.
wd	Character object defining file path where dl_models folder will be created and deep learning models saved. Defaults to current working directory.
folds	Character object defining number of folds for xval. Default is NULL and currently is not implemented.
rf_min_depth	Numeric object which sets the minimum tree depth for all random forest models. Defaut is 1.
rf_max_depth	Numeric object which sets the maximum tree depth for all random forest models. Defaut is 7.
rf_runtime_secs	Numeric object defining total number of seconds the hyper parameter grid search will run.
rf_stopping_rounds	Numeric object defining maximum number of training rounds an individual deep learning model not improving will continue to run. Default is 10.
rf_stopping_tolerance	Numeric object which sets the mimmum loss funciton improvement for a training iteration to be considered an improvement. Defulat is 1E-5.
grid_strategy	Character object default and only current supported option is "randomDiscrete"

Value

List object containing H2O model objects. Additionally saves h2o models as re-loadable text files in wd/rf_models folder.

andrewsommerlot/startml documentation built on May 5, 2019, 6:58 p.m.