public static class KMeansModel.KMeansOutput
extends hex.ClusteringModel.ClusteringOutput
| Modifier and Type | Field and Description |
|---|---|
double[] |
_avg_centroids_chg |
double |
_betweenss |
int |
_categorical_column_count |
double[] |
_history_withinss |
int |
_iterations |
long[] |
_size |
double |
_tot_withinss |
double |
_totss |
long[] |
_training_time_ms |
double[] |
_withinss |
_centers_raw, _centers_std_raw, _normMul, _normSub_cross_validation_metrics, _cross_validation_models, _cross_validation_predictions, _distribution, _domains, _end_time, _hasFold, _hasOffset, _hasWeights, _isSupervised, _model_metrics, _model_summary, _modelClassDist, _names, _priorClassDist, _run_time, _scoring_history, _start_time, _status, _training_metrics, _validation_metrics| Constructor and Description |
|---|
KMeansModel.KMeansOutput(KMeans b) |
getModelCategory, isSupervised, nclassesaddModelMetrics, classNames, foldIdx, foldName, hasFold, hasOffset, hasWeights, isClassifier, nfeatures, offsetIdx, offsetName, printTwoDimTables, responseIdx, responseName, toString, weightsIdx, weightsNamepublic int _iterations
public double[] _avg_centroids_chg
public double[] _withinss
public long[] _size
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 KMeansModel.KMeansOutput(KMeans b)