public abstract static class ClusteringModel.ClusteringParameters extends Model.Parameters
Model.Parameters.CategoricalEncodingScheme, Model.Parameters.FoldAssignmentScheme
Modifier and Type | Field and Description |
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int |
_k
Clustering models must specify the number of clusters to generate
|
_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 |
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ClusteringParameters() |
algoName, checksum, checksum, defaultDropConsCols, defaultStoppingTolerance, fullName, getCategoricalEncoding, getDependentKeys, getDistributionFamily, getFoldColumn, getMaxCategoricalLevels, getNonPredictors, getOffsetColumn, getOrMakeRealSeed, getResponseColumn, getTreatmentColumn, getUsedColumns, getWeightsColumn, hasCheckpoint, javaName, missingColumnsType, progressUnits, read_lock_frames, read_unlock_frames, setDistributionFamily, setTrain, train, valid
asBytes, clone, copyOver, frozenType, read, readExternal, readJSON, reloadFromBytes, toJsonBytes, toJsonString, write, writeExternal, writeJSON