public static class AggregatorModel.AggregatorParameters
extends hex.Model.Parameters
Modifier and Type | Field and Description |
---|---|
int |
_k |
PCAModel.PCAParameters.Method |
_pca_method |
double |
_rel_tol_num_exemplars |
int |
_target_num_exemplars |
DataInfo.TransformType |
_transform |
boolean |
_use_all_factor_levels |
_auto_rebalance, _balance_classes, _categorical_encoding, _checkpoint, _class_sampling_factors, _distribution, _fold_assignment, _fold_column, _huber_alpha, _ignore_const_cols, _ignored_columns, _is_cv_model, _keep_cross_validation_fold_assignment, _keep_cross_validation_predictions, _max_after_balance_size, _max_categorical_levels, _max_confusion_matrix_size, _max_runtime_secs, _nfolds, _offset_column, _parallelize_cross_validation, _pretrained_autoencoder, _quantile_alpha, _response_column, _score_each_iteration, _seed, _stopping_metric, _stopping_rounds, _stopping_tolerance, _train, _tweedie_power, _valid, _weights_column, MAX_SUPPORTED_LEVELS
Constructor and Description |
---|
AggregatorModel.AggregatorParameters() |
Modifier and Type | Method and Description |
---|---|
java.lang.String |
algoName() |
java.lang.String |
fullName() |
java.lang.String |
javaName() |
long |
progressUnits() |
checksum_impl, checksum, defaultDropConsCols, defaultStoppingTolerance, getOrMakeRealSeed, hasCheckpoint, missingColumnsType, read_lock_frames, read_unlock_frames, setTrain, train, valid
public DataInfo.TransformType _transform
public PCAModel.PCAParameters.Method _pca_method
public int _k
public int _target_num_exemplars
public double _rel_tol_num_exemplars
public boolean _use_all_factor_levels
public AggregatorModel.AggregatorParameters()
public java.lang.String algoName()
algoName
in class hex.Model.Parameters
public java.lang.String fullName()
fullName
in class hex.Model.Parameters
public java.lang.String javaName()
javaName
in class hex.Model.Parameters
public long progressUnits()
progressUnits
in class hex.Model.Parameters