public static class ModelSelectionModel.ModelSelectionParameters
extends hex.Model.Parameters
| Modifier and Type | Class and Description |
|---|---|
static class |
ModelSelectionModel.ModelSelectionParameters.Mode |
| Modifier and Type | Field and Description |
|---|---|
double[] |
_alpha |
boolean |
_compute_p_values |
java.lang.String[] |
_interactions |
double[] |
_lambda |
boolean |
_lambda_search |
GLMModel.GLMParameters.Link |
_link |
int |
_max_predictor_number |
java.io.Serializable |
_missing_values_handling |
ModelSelectionModel.ModelSelectionParameters.Mode |
_mode |
int |
_nfolds |
int |
_nparallelism |
water.Key<water.fvec.Frame> |
_plug_values |
boolean |
_remove_collinear_columns |
GLMModel.GLMParameters.Solver |
_solver |
boolean |
_standardize |
_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, _max_after_balance_size, _max_categorical_levels, _max_confusion_matrix_size, _max_runtime_secs, _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 |
|---|
ModelSelectionParameters() |
| Modifier and Type | Method and Description |
|---|---|
java.lang.String |
algoName() |
java.lang.String |
fullName() |
boolean |
imputeMissing() |
java.lang.String |
javaName() |
DataInfo.Imputer |
makeImputer() |
GLMModel.GLMParameters.MissingValuesHandling |
missingValuesHandling() |
long |
progressUnits() |
checksum, checksum, defaultDropConsCols, defaultStoppingTolerance, getCategoricalEncoding, getDependentKeys, getFoldColumn, getMaxCategoricalLevels, getNonPredictors, getOffsetColumn, getOrMakeRealSeed, getResponseColumn, getTreatmentColumn, getUsedColumns, getWeightsColumn, hasCheckpoint, missingColumnsType, read_lock_frames, read_unlock_frames, setTrain, train, validpublic double[] _alpha
public double[] _lambda
public boolean _standardize
public boolean _lambda_search
public GLMModel.GLMParameters.Link _link
public GLMModel.GLMParameters.Solver _solver
public java.lang.String[] _interactions
public java.io.Serializable _missing_values_handling
public boolean _compute_p_values
public boolean _remove_collinear_columns
public int _nfolds
public water.Key<water.fvec.Frame> _plug_values
public int _max_predictor_number
public int _nparallelism
public ModelSelectionModel.ModelSelectionParameters.Mode _mode
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 GLMModel.GLMParameters.MissingValuesHandling missingValuesHandling()
public boolean imputeMissing()
public DataInfo.Imputer makeImputer()