public class KMeansParametersV3 extends ClusteringModelParametersSchemaV3
| Modifier and Type | Field and Description |
|---|---|
boolean |
estimateK
Whether to estimate the number of clusters (<=k) iteratively and deterministically.
|
KMeansInitialization |
init
Initialization mode
|
int |
maxIterations
Maximum training iterations (if estimate_k is enabled, then this is for each inner Lloyds iteration)
|
long |
seed
RNG Seed
|
boolean |
standardize
Standardize columns before computing distances
|
FrameKeyV3 |
userPoints
User-specified points
|
kcategoricalEncoding, checkpoint, distribution, foldAssignment, foldColumn, huberAlpha, ignoreConstCols, ignoredColumns, keepCrossValidationFoldAssignment, keepCrossValidationPredictions, maxRuntimeSecs, modelId, nfolds, offsetColumn, parallelizeCrossValidation, quantileAlpha, responseColumn, scoreEachIteration, stoppingMetric, stoppingRounds, stoppingTolerance, trainingFrame, tweediePower, validationFrame, weightsColumn| Constructor and Description |
|---|
KMeansParametersV3()
Public constructor
|
| Modifier and Type | Method and Description |
|---|---|
java.lang.String |
toString()
Return the contents of this object as a JSON String.
|
public FrameKeyV3 userPoints
public int maxIterations
public boolean standardize
public long seed
public KMeansInitialization init
public boolean estimateK
public java.lang.String toString()
toString in class ClusteringModelParametersSchemaV3