Description Usage Arguments Value
gbm_autogrid is a wrapper employing built-in settings to run grid search hyper parameter optimizations on gradient boosted machine algorithm.
1 2 3 4 | gbm_autogrid(train, valid, y, x, eval_metric = "AUTO", wd = getwd(),
folds = NULL, gbm_min_depth = 1, gbm_max_depth = 7,
gbm_runtime_secs = 10, gbm_stopping_rounds = 10,
gbm_stopping_tolerance = 1e-05, grid_strategy = "RandomDiscrete")
|
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. |
gbm_min_depth |
Numeric object which sets the mimmum loss funciton improvement for a training iteration to be considered an improvement. Defulat is 1E-5. |
gbm_max_depth |
Numeric object which sets the maximum tree depth for all gbm models. Defulat is 7. |
gbm_runtime_secs |
Numeric object defining total number of seconds the hyper parameter grid search will run. |
gbm_stopping_rounds |
Numeric object defining maximum number of training rounds an individual deep learning model not improving will continue to run. Default is 10. |
gbm_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" |
List object containing H2O model objects. Additionally saves h2o models as re-loadable text files in wd/gbm_models folder.
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