public static class NaiveBayesModel.NaiveBayesParameters
extends hex.Model.Parameters
Modifier and Type | Field and Description |
---|---|
boolean |
_compute_metrics |
double |
_eps_prob |
double |
_eps_sdev |
double |
_laplace |
double |
_min_prob |
double |
_min_sdev |
_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 |
---|
NaiveBayesModel.NaiveBayesParameters() |
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 double _laplace
public double _eps_sdev
public double _min_sdev
public double _eps_prob
public double _min_prob
public boolean _compute_metrics
public NaiveBayesModel.NaiveBayesParameters()
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