public static class PSVMModel.PSVMParameters
extends hex.Model.Parameters
| Modifier and Type | Field and Description |
|---|---|
boolean |
_disable_training_metrics |
double |
_fact_threshold |
double |
_feasible_threshold |
double |
_gamma |
double |
_hyper_param |
hex.genmodel.algos.psvm.KernelType |
_kernel_type |
int |
_max_iterations |
double |
_mu_factor |
double |
_negative_weight |
double |
_positive_weight |
double |
_rank_ratio |
long |
_seed |
double |
_surrogate_gap_threshold |
double |
_sv_threshold |
double |
_zero_threshold |
_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, _stopping_metric, _stopping_rounds, _stopping_tolerance, _train, _treatment_column, _tweedie_power, _valid, _weights_column, MAX_SUPPORTED_LEVELS| Constructor and Description |
|---|
PSVMParameters() |
| Modifier and Type | Method and Description |
|---|---|
java.lang.String |
algoName() |
java.lang.String |
fullName() |
java.lang.String |
javaName() |
Kernel |
kernel() |
long |
progressUnits() |
checksum, checksum, defaultDropConsCols, defaultStoppingTolerance, getCategoricalEncoding, getDependentKeys, getDistributionFamily, getFoldColumn, getMaxCategoricalLevels, getNonPredictors, getOffsetColumn, getOrMakeRealSeed, getResponseColumn, getTreatmentColumn, getUsedColumns, getWeightsColumn, hasCheckpoint, hasCustomMetricFunc, missingColumnsType, read_lock_frames, read_unlock_frames, setDistributionFamily, setTrain, train, validpublic long _seed
public double _hyper_param
public double _positive_weight
public double _negative_weight
public double _sv_threshold
public double _zero_threshold
public boolean _disable_training_metrics
public hex.genmodel.algos.psvm.KernelType _kernel_type
public double _gamma
public double _rank_ratio
public double _fact_threshold
public int _max_iterations
public double _feasible_threshold
public double _surrogate_gap_threshold
public double _mu_factor
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 Kernel kernel()