public static class KMeansModel.KMeansOutput
extends hex.ClusteringModel.ClusteringOutput
Modifier and Type | Field and Description |
---|---|
double |
_betweenss |
int |
_categorical_column_count |
double[] |
_history_withinss |
int |
_iterations |
int[] |
_k |
double[] |
_reassigned_count |
double |
_tot_withinss |
double |
_totss |
long[] |
_training_time_ms |
double[] |
_withinss |
_centers_raw, _centers_std_raw, _mode, _normMul, _normSub, _size
_cross_validation_fold_assignment_frame_id, _cross_validation_holdout_predictions_frame_id, _cross_validation_metrics, _cross_validation_metrics_summary, _cross_validation_models, _cross_validation_predictions, _distribution, _domains, _end_time, _hasFold, _hasOffset, _hasWeights, _isSupervised, _job, _model_summary, _modelClassDist, _names, _origDomains, _origNames, _priorClassDist, _run_time, _scoring_history, _start_time, _training_metrics, _validation_metrics
Constructor and Description |
---|
KMeansModel.KMeansOutput(KMeans b) |
getModelCategory, isSupervised, nclasses
checksum_impl, classNames, clearModelMetrics, foldIdx, foldName, getModelMetrics, hasFold, hasOffset, hasWeights, interactions, isAutoencoder, isBinomialClassifier, isClassifier, nfeatures, offsetIdx, offsetName, printTwoDimTables, responseIdx, responseName, setNames, startClock, stopClock, toString, weightsIdx, weightsName
public int _iterations
public double[] _withinss
public double _tot_withinss
public double[] _history_withinss
public double _totss
public double _betweenss
public int _categorical_column_count
public long[] _training_time_ms
public double[] _reassigned_count
public int[] _k
public KMeansModel.KMeansOutput(KMeans b)