Arguments
x
A vector containing the names or indices of the predictor variables to use in building the model.
If x is missing,then all columns except y are used.
y
The name of the response variable in the model.If the data does not contain a header, this is the column index
number starting at 0, and increasing from left to right. (The response must be either an integer or a
categorical variable).
training_frame
Id of the training data frame (Not required, to allow initial validation of model parameters).
model_id
Destination id for this model; auto-generated if not specified.
validation_frame
Id of the validation data frame.
base_models
List of model ids which we can stack together. Which ones are chosen depends on the selection_strategy
(currently, all models will be used since selection_strategy can only be set to choose_all). Models must have
been cross-validated using nfolds > 1, fold_assignment equal to Modulo, and keep_cross_validation_folds must
be set to True. Defaults to [].
selection_strategy
Strategy for choosing which models to stack. Must be one of: "choose_all".