public static class StackedEnsembleModel.StackedEnsembleParameters
extends hex.Model.Parameters
| Modifier and Type | Class and Description |
|---|---|
static class |
StackedEnsembleModel.StackedEnsembleParameters.MetalearnerTransform |
| Modifier and Type | Field and Description |
|---|---|
water.Key<hex.Model>[] |
_base_models |
water.Key<water.fvec.Frame> |
_blending |
boolean |
_keep_base_model_predictions |
boolean |
_keep_levelone_frame |
Metalearner.Algorithm |
_metalearner_algorithm |
hex.Model.Parameters.FoldAssignmentScheme |
_metalearner_fold_assignment |
java.lang.String |
_metalearner_fold_column |
int |
_metalearner_nfolds |
hex.Model.Parameters |
_metalearner_parameters |
java.lang.String |
_metalearner_params |
StackedEnsembleModel.StackedEnsembleParameters.MetalearnerTransform |
_metalearner_transform |
long |
_score_training_samples |
_auc_type, _auto_rebalance, _auuc_nbins, _auuc_type, _balance_classes, _categorical_encoding, _check_constant_response, _checkpoint, _class_sampling_factors, _custom_distribution_func, _custom_metric_func, _cv_fold, _distribution, _export_checkpoints_dir, _fold_assignment, _fold_column, _gainslift_bins, _huber_alpha, _ignore_const_cols, _ignored_columns, _is_cv_model, _keep_cross_validation_fold_assignment, _keep_cross_validation_models, _keep_cross_validation_predictions, _keep_cross_validation_predictions_precision, _main_model_time_budget_factor, _max_after_balance_size, _max_categorical_levels, _max_confusion_matrix_size, _max_runtime_secs, _nfolds, _offset_column, _parallelize_cross_validation, _preprocessors, _pretrained_autoencoder, _quantile_alpha, _response_column, _score_each_iteration, _seed, _stopping_metric, _stopping_rounds, _stopping_tolerance, _train, _treatment_column, _tweedie_power, _valid, _weights_column, MAX_SUPPORTED_LEVELS| Constructor and Description |
|---|
StackedEnsembleParameters() |
| Modifier and Type | Method and Description |
|---|---|
java.lang.String |
algoName() |
water.fvec.Frame |
blending() |
java.lang.String |
fullName() |
hex.genmodel.utils.DistributionFamily |
getDistributionFamily() |
java.lang.String[] |
getNonPredictors() |
void |
initMetalearnerParams()
initialize
_metalearner_parameters with default parameters for the current _metalearner_algorithm. |
void |
initMetalearnerParams(Metalearner.Algorithm algo)
initialize
_metalearner_parameters with default parameters for the given algorithm |
java.lang.String |
javaName() |
long |
progressUnits() |
void |
setDistributionFamily(hex.genmodel.utils.DistributionFamily distributionFamily) |
checksum, checksum, defaultDropConsCols, defaultStoppingTolerance, getCategoricalEncoding, getDependentKeys, getFoldColumn, getMaxCategoricalLevels, getOffsetColumn, getOrMakeRealSeed, getResponseColumn, getTreatmentColumn, getUsedColumns, getWeightsColumn, hasCheckpoint, hasCustomMetricFunc, missingColumnsType, read_lock_frames, read_unlock_frames, setTrain, train, validpublic water.Key<hex.Model>[] _base_models
public boolean _keep_levelone_frame
public boolean _keep_base_model_predictions
public int _metalearner_nfolds
public hex.Model.Parameters.FoldAssignmentScheme _metalearner_fold_assignment
public java.lang.String _metalearner_fold_column
public water.Key<water.fvec.Frame> _blending
public StackedEnsembleModel.StackedEnsembleParameters.MetalearnerTransform _metalearner_transform
public Metalearner.Algorithm _metalearner_algorithm
public java.lang.String _metalearner_params
public hex.Model.Parameters _metalearner_parameters
public long _score_training_samples
public java.lang.String algoName()
algoName in class hex.Model.Parameterspublic java.lang.String fullName()
fullName in class hex.Model.Parameterspublic java.lang.String javaName()
javaName in class hex.Model.Parameterspublic long progressUnits()
progressUnits in class hex.Model.Parameterspublic void initMetalearnerParams()
_metalearner_parameters with default parameters for the current _metalearner_algorithm.public void initMetalearnerParams(Metalearner.Algorithm algo)
_metalearner_parameters with default parameters for the given algorithmalgo - the metalearner algorithm we want to use and for which parameters are initialized.public final water.fvec.Frame blending()
public java.lang.String[] getNonPredictors()
getNonPredictors in interface hex.Model.AdaptFrameParametersgetNonPredictors in class hex.Model.Parameterspublic hex.genmodel.utils.DistributionFamily getDistributionFamily()
getDistributionFamily in class hex.Model.Parameterspublic void setDistributionFamily(hex.genmodel.utils.DistributionFamily distributionFamily)
setDistributionFamily in class hex.Model.Parameters