KMeansModel (Spark 3.5.5 JavaDoc) (original) (raw)

Object
- org.apache.spark.ml.PipelineStage
- - org.apache.spark.ml.Transformer
    - - org.apache.spark.ml.Model<KMeansModel>
        * * org.apache.spark.ml.clustering.KMeansModel
All Implemented Interfaces:
java.io.Serializable, org.apache.spark.internal.Logging, KMeansParams, Params, HasDistanceMeasure, HasFeaturesCol, HasMaxBlockSizeInMB, HasMaxIter, HasPredictionCol, HasSeed, HasSolver, HasTol, HasWeightCol, GeneralMLWritable, HasTrainingSummary<KMeansSummary>, Identifiable, MLWritable

public class KMeansModel
extends Model<KMeansModel>
implements KMeansParams, GeneralMLWritable, HasTrainingSummary<KMeansSummary>
Model fitted by KMeans.
param: parentModel a model trained by spark.mllib.clustering.KMeans.
See Also:
Serialized Form

Nested Class Summary

 * ### Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging  
 `org.apache.spark.internal.Logging.SparkShellLoggingFilter`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods

Modifier and Type	Method and Description
Vector[]	clusterCenters()
KMeansModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
Param	distanceMeasure() Param for The distance measure.
Param	featuresCol() Param for features column name.
Param	initMode() Param for the initialization algorithm.
IntParam	initSteps() Param for the number of steps for the k-means\|
IntParam	k() The number of clusters to create (k).
static KMeansModel	load(String path)
DoubleParam	maxBlockSizeInMB() Param for Maximum memory in MB for stacking input data into blocks.
IntParam	maxIter() Param for maximum number of iterations (>= 0).
int	numFeatures()
int	predict(Vector features)
Param	predictionCol() Param for prediction column name.
static MLReader<KMeansModel>	read()
LongParam	seed() Param for random seed.
KMeansModel	setFeaturesCol(String value)
KMeansModel	setPredictionCol(String value)
Param	solver() Param for the name of optimization method used in KMeans.
KMeansSummary	summary() Gets summary of model on training set.
DoubleParam	tol() Param for the convergence tolerance for iterative algorithms (>= 0).
String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) Check transform validity and derive the output schema from the input schema.
String	uid() An immutable unique ID for the object and its derivatives.
Param	weightCol() Param for weight column name.
GeneralMLWriter	write() Returns a GeneralMLWriter instance for this ML instance.

   * ### Methods inherited from class org.apache.spark.ml.[Model](../../../../../org/apache/spark/ml/Model.html "class in org.apache.spark.ml")  
   `[hasParent](../../../../../org/apache/spark/ml/Model.html#hasParent--), [parent](../../../../../org/apache/spark/ml/Model.html#parent--), [setParent](../../../../../org/apache/spark/ml/Model.html#setParent-org.apache.spark.ml.Estimator-)`  
   * ### Methods inherited from class org.apache.spark.ml.[Transformer](../../../../../org/apache/spark/ml/Transformer.html "class in org.apache.spark.ml")  
   `[transform](../../../../../org/apache/spark/ml/Transformer.html#transform-org.apache.spark.sql.Dataset-org.apache.spark.ml.param.ParamMap-), [transform](../../../../../org/apache/spark/ml/Transformer.html#transform-org.apache.spark.sql.Dataset-org.apache.spark.ml.param.ParamPair-org.apache.spark.ml.param.ParamPair...-), [transform](../../../../../org/apache/spark/ml/Transformer.html#transform-org.apache.spark.sql.Dataset-org.apache.spark.ml.param.ParamPair-scala.collection.Seq-)`  
   * ### Methods inherited from class org.apache.spark.ml.[PipelineStage](../../../../../org/apache/spark/ml/PipelineStage.html "class in org.apache.spark.ml")  
   `[params](../../../../../org/apache/spark/ml/PipelineStage.html#params--)`  
   * ### Methods inherited from class Object  
   `equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`  
   * ### Methods inherited from interface org.apache.spark.ml.clustering.[KMeansParams](../../../../../org/apache/spark/ml/clustering/KMeansParams.html "interface in org.apache.spark.ml.clustering")  
   `[getInitMode](../../../../../org/apache/spark/ml/clustering/KMeansParams.html#getInitMode--), [getInitSteps](../../../../../org/apache/spark/ml/clustering/KMeansParams.html#getInitSteps--), [getK](../../../../../org/apache/spark/ml/clustering/KMeansParams.html#getK--), [validateAndTransformSchema](../../../../../org/apache/spark/ml/clustering/KMeansParams.html#validateAndTransformSchema-org.apache.spark.sql.types.StructType-)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html "interface in org.apache.spark.ml.param.shared")  
   `[getMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html#getMaxIter--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasFeaturesCol](../../../../../org/apache/spark/ml/param/shared/HasFeaturesCol.html "interface in org.apache.spark.ml.param.shared")  
   `[getFeaturesCol](../../../../../org/apache/spark/ml/param/shared/HasFeaturesCol.html#getFeaturesCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasSeed](../../../../../org/apache/spark/ml/param/shared/HasSeed.html "interface in org.apache.spark.ml.param.shared")  
   `[getSeed](../../../../../org/apache/spark/ml/param/shared/HasSeed.html#getSeed--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasPredictionCol](../../../../../org/apache/spark/ml/param/shared/HasPredictionCol.html "interface in org.apache.spark.ml.param.shared")  
   `[getPredictionCol](../../../../../org/apache/spark/ml/param/shared/HasPredictionCol.html#getPredictionCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html "interface in org.apache.spark.ml.param.shared")  
   `[getTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html#getTol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasDistanceMeasure](../../../../../org/apache/spark/ml/param/shared/HasDistanceMeasure.html "interface in org.apache.spark.ml.param.shared")  
   `[getDistanceMeasure](../../../../../org/apache/spark/ml/param/shared/HasDistanceMeasure.html#getDistanceMeasure--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasWeightCol](../../../../../org/apache/spark/ml/param/shared/HasWeightCol.html "interface in org.apache.spark.ml.param.shared")  
   `[getWeightCol](../../../../../org/apache/spark/ml/param/shared/HasWeightCol.html#getWeightCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasSolver](../../../../../org/apache/spark/ml/param/shared/HasSolver.html "interface in org.apache.spark.ml.param.shared")  
   `[getSolver](../../../../../org/apache/spark/ml/param/shared/HasSolver.html#getSolver--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasMaxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html "interface in org.apache.spark.ml.param.shared")  
   `[getMaxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html#getMaxBlockSizeInMB--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.[Params](../../../../../org/apache/spark/ml/param/Params.html "interface in org.apache.spark.ml.param")  
   `[clear](../../../../../org/apache/spark/ml/param/Params.html#clear-org.apache.spark.ml.param.Param-), [copyValues](../../../../../org/apache/spark/ml/param/Params.html#copyValues-T-org.apache.spark.ml.param.ParamMap-), [defaultCopy](../../../../../org/apache/spark/ml/param/Params.html#defaultCopy-org.apache.spark.ml.param.ParamMap-), [defaultParamMap](../../../../../org/apache/spark/ml/param/Params.html#defaultParamMap--), [explainParam](../../../../../org/apache/spark/ml/param/Params.html#explainParam-org.apache.spark.ml.param.Param-), [explainParams](../../../../../org/apache/spark/ml/param/Params.html#explainParams--), [extractParamMap](../../../../../org/apache/spark/ml/param/Params.html#extractParamMap--), [extractParamMap](../../../../../org/apache/spark/ml/param/Params.html#extractParamMap-org.apache.spark.ml.param.ParamMap-), [get](../../../../../org/apache/spark/ml/param/Params.html#get-org.apache.spark.ml.param.Param-), [getDefault](../../../../../org/apache/spark/ml/param/Params.html#getDefault-org.apache.spark.ml.param.Param-), [getOrDefault](../../../../../org/apache/spark/ml/param/Params.html#getOrDefault-org.apache.spark.ml.param.Param-), [getParam](../../../../../org/apache/spark/ml/param/Params.html#getParam-java.lang.String-), [hasDefault](../../../../../org/apache/spark/ml/param/Params.html#hasDefault-org.apache.spark.ml.param.Param-), [hasParam](../../../../../org/apache/spark/ml/param/Params.html#hasParam-java.lang.String-), [isDefined](../../../../../org/apache/spark/ml/param/Params.html#isDefined-org.apache.spark.ml.param.Param-), [isSet](../../../../../org/apache/spark/ml/param/Params.html#isSet-org.apache.spark.ml.param.Param-), [onParamChange](../../../../../org/apache/spark/ml/param/Params.html#onParamChange-org.apache.spark.ml.param.Param-), [paramMap](../../../../../org/apache/spark/ml/param/Params.html#paramMap--), [params](../../../../../org/apache/spark/ml/param/Params.html#params--), [set](../../../../../org/apache/spark/ml/param/Params.html#set-org.apache.spark.ml.param.Param-T-), [set](../../../../../org/apache/spark/ml/param/Params.html#set-org.apache.spark.ml.param.ParamPair-), [set](../../../../../org/apache/spark/ml/param/Params.html#set-java.lang.String-java.lang.Object-), [setDefault](../../../../../org/apache/spark/ml/param/Params.html#setDefault-org.apache.spark.ml.param.Param-T-), [setDefault](../../../../../org/apache/spark/ml/param/Params.html#setDefault-scala.collection.Seq-), [shouldOwn](../../../../../org/apache/spark/ml/param/Params.html#shouldOwn-org.apache.spark.ml.param.Param-)`  
   * ### Methods inherited from interface org.apache.spark.ml.util.[MLWritable](../../../../../org/apache/spark/ml/util/MLWritable.html "interface in org.apache.spark.ml.util")  
   `[save](../../../../../org/apache/spark/ml/util/MLWritable.html#save-java.lang.String-)`  
   * ### Methods inherited from interface org.apache.spark.ml.util.[HasTrainingSummary](../../../../../org/apache/spark/ml/util/HasTrainingSummary.html "interface in org.apache.spark.ml.util")  
   `[hasSummary](../../../../../org/apache/spark/ml/util/HasTrainingSummary.html#hasSummary--), [setSummary](../../../../../org/apache/spark/ml/util/HasTrainingSummary.html#setSummary-scala.Option-)`  
   * ### Methods inherited from interface org.apache.spark.internal.Logging  
   `$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize`

Method Detail

 * #### read  
 public static [MLReader](../../../../../org/apache/spark/ml/util/MLReader.html "class in org.apache.spark.ml.util")<[KMeansModel](../../../../../org/apache/spark/ml/clustering/KMeansModel.html "class in org.apache.spark.ml.clustering")> read()  
 * #### load  
 public static [KMeansModel](../../../../../org/apache/spark/ml/clustering/KMeansModel.html "class in org.apache.spark.ml.clustering") load(String path)  
 * #### k  
 public final [IntParam](../../../../../org/apache/spark/ml/param/IntParam.html "class in org.apache.spark.ml.param") k()  
 The number of clusters to create (k). Must be &gt; 1\. Note that it is possible for fewer than k clusters to be returned, for example, if there are fewer than k distinct points to cluster. Default: 2.  
 Specified by:  
 `[k](../../../../../org/apache/spark/ml/clustering/KMeansParams.html#k--)` in interface `[KMeansParams](../../../../../org/apache/spark/ml/clustering/KMeansParams.html "interface in org.apache.spark.ml.clustering")`  
 Returns:  
 (undocumented)  
 * #### initMode  
 public final [Param](../../../../../org/apache/spark/ml/param/Param.html "class in org.apache.spark.ml.param")<String> initMode()  
 Param for the initialization algorithm. This can be either "random" to choose random points as initial cluster centers, or "k-means||" to use a parallel variant of k-means++ (Bahmani et al., Scalable K-Means++, VLDB 2012). Default: k-means||.  
 Specified by:  
 `[initMode](../../../../../org/apache/spark/ml/clustering/KMeansParams.html#initMode--)` in interface `[KMeansParams](../../../../../org/apache/spark/ml/clustering/KMeansParams.html "interface in org.apache.spark.ml.clustering")`  
 Returns:  
 (undocumented)  
 * #### initSteps  
 public final [IntParam](../../../../../org/apache/spark/ml/param/IntParam.html "class in org.apache.spark.ml.param") initSteps()  
 Param for the number of steps for the k-means|| initialization mode. This is an advanced setting -- the default of 2 is almost always enough. Must be &gt; 0\. Default: 2.  
 Specified by:  
 `[initSteps](../../../../../org/apache/spark/ml/clustering/KMeansParams.html#initSteps--)` in interface `[KMeansParams](../../../../../org/apache/spark/ml/clustering/KMeansParams.html "interface in org.apache.spark.ml.clustering")`  
 Returns:  
 (undocumented)  
 * #### solver  
 public final [Param](../../../../../org/apache/spark/ml/param/Param.html "class in org.apache.spark.ml.param")<String> solver()  
 Param for the name of optimization method used in KMeans. Supported options: - "auto": Automatically select the solver based on the input schema and sparsity: If input instances are arrays or input vectors are dense, set to "block". Else, set to "row". - "row": input instances are processed row by row, and triangle-inequality is applied to accelerate the training. - "block": input instances are stacked to blocks, and GEMM is applied to compute the distances. Default is "auto".  
 Specified by:  
 `[solver](../../../../../org/apache/spark/ml/clustering/KMeansParams.html#solver--)` in interface `[KMeansParams](../../../../../org/apache/spark/ml/clustering/KMeansParams.html "interface in org.apache.spark.ml.clustering")`  
 Specified by:  
 `[solver](../../../../../org/apache/spark/ml/param/shared/HasSolver.html#solver--)` in interface `[HasSolver](../../../../../org/apache/spark/ml/param/shared/HasSolver.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### maxBlockSizeInMB  
 public final [DoubleParam](../../../../../org/apache/spark/ml/param/DoubleParam.html "class in org.apache.spark.ml.param") maxBlockSizeInMB()  
 Param for Maximum memory in MB for stacking input data into blocks. Data is stacked within partitions. If more than remaining data size in a partition then it is adjusted to the data size. Default 0.0 represents choosing optimal value, depends on specific algorithm. Must be &gt;= 0..  
 Specified by:  
 `[maxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html#maxBlockSizeInMB--)` in interface `[HasMaxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### weightCol  
 public final [Param](../../../../../org/apache/spark/ml/param/Param.html "class in org.apache.spark.ml.param")<String> weightCol()  
 Param for weight column name. If this is not set or empty, we treat all instance weights as 1.0.  
 Specified by:  
 `[weightCol](../../../../../org/apache/spark/ml/param/shared/HasWeightCol.html#weightCol--)` in interface `[HasWeightCol](../../../../../org/apache/spark/ml/param/shared/HasWeightCol.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### distanceMeasure  
 public final [Param](../../../../../org/apache/spark/ml/param/Param.html "class in org.apache.spark.ml.param")<String> distanceMeasure()  
 Param for The distance measure. Supported options: 'euclidean' and 'cosine'.  
 Specified by:  
 `[distanceMeasure](../../../../../org/apache/spark/ml/param/shared/HasDistanceMeasure.html#distanceMeasure--)` in interface `[HasDistanceMeasure](../../../../../org/apache/spark/ml/param/shared/HasDistanceMeasure.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### tol  
 public final [DoubleParam](../../../../../org/apache/spark/ml/param/DoubleParam.html "class in org.apache.spark.ml.param") tol()  
 Description copied from interface: `[HasTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html#tol--)`  
 Param for the convergence tolerance for iterative algorithms (&gt;= 0).  
 Specified by:  
 `[tol](../../../../../org/apache/spark/ml/param/shared/HasTol.html#tol--)` in interface `[HasTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### predictionCol  
 public final [Param](../../../../../org/apache/spark/ml/param/Param.html "class in org.apache.spark.ml.param")<String> predictionCol()  
 Param for prediction column name.  
 Specified by:  
 `[predictionCol](../../../../../org/apache/spark/ml/param/shared/HasPredictionCol.html#predictionCol--)` in interface `[HasPredictionCol](../../../../../org/apache/spark/ml/param/shared/HasPredictionCol.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### seed  
 public final [LongParam](../../../../../org/apache/spark/ml/param/LongParam.html "class in org.apache.spark.ml.param") seed()  
 Description copied from interface: `[HasSeed](../../../../../org/apache/spark/ml/param/shared/HasSeed.html#seed--)`  
 Param for random seed.  
 Specified by:  
 `[seed](../../../../../org/apache/spark/ml/param/shared/HasSeed.html#seed--)` in interface `[HasSeed](../../../../../org/apache/spark/ml/param/shared/HasSeed.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### featuresCol  
 public final [Param](../../../../../org/apache/spark/ml/param/Param.html "class in org.apache.spark.ml.param")<String> featuresCol()  
 Param for features column name.  
 Specified by:  
 `[featuresCol](../../../../../org/apache/spark/ml/param/shared/HasFeaturesCol.html#featuresCol--)` in interface `[HasFeaturesCol](../../../../../org/apache/spark/ml/param/shared/HasFeaturesCol.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### maxIter  
 public final [IntParam](../../../../../org/apache/spark/ml/param/IntParam.html "class in org.apache.spark.ml.param") maxIter()  
 Description copied from interface: `[HasMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html#maxIter--)`  
 Param for maximum number of iterations (&gt;= 0).  
 Specified by:  
 `[maxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html#maxIter--)` in interface `[HasMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html "interface in org.apache.spark.ml.param.shared")`  
 Returns:  
 (undocumented)  
 * #### uid  
 public String uid()  
 An immutable unique ID for the object and its derivatives.  
 Specified by:  
 `[uid](../../../../../org/apache/spark/ml/util/Identifiable.html#uid--)` in interface `[Identifiable](../../../../../org/apache/spark/ml/util/Identifiable.html "interface in org.apache.spark.ml.util")`  
 Returns:  
 (undocumented)  
 * #### numFeatures  
 public int numFeatures()  
 * #### copy  
 public [KMeansModel](../../../../../org/apache/spark/ml/clustering/KMeansModel.html "class in org.apache.spark.ml.clustering") copy([ParamMap](../../../../../org/apache/spark/ml/param/ParamMap.html "class in org.apache.spark.ml.param") extra)  
 Description copied from interface: `[Params](../../../../../org/apache/spark/ml/param/Params.html#copy-org.apache.spark.ml.param.ParamMap-)`  
 Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See `defaultCopy()`.  
 Specified by:  
 `[copy](../../../../../org/apache/spark/ml/param/Params.html#copy-org.apache.spark.ml.param.ParamMap-)` in interface `[Params](../../../../../org/apache/spark/ml/param/Params.html "interface in org.apache.spark.ml.param")`  
 Specified by:  
 `[copy](../../../../../org/apache/spark/ml/Model.html#copy-org.apache.spark.ml.param.ParamMap-)` in class `[Model](../../../../../org/apache/spark/ml/Model.html "class in org.apache.spark.ml")<[KMeansModel](../../../../../org/apache/spark/ml/clustering/KMeansModel.html "class in org.apache.spark.ml.clustering")>`  
 Parameters:  
 `extra` \- (undocumented)  
 Returns:  
 (undocumented)  
 * #### setFeaturesCol  
 public [KMeansModel](../../../../../org/apache/spark/ml/clustering/KMeansModel.html "class in org.apache.spark.ml.clustering") setFeaturesCol(String value)  
 * #### setPredictionCol  
 public [KMeansModel](../../../../../org/apache/spark/ml/clustering/KMeansModel.html "class in org.apache.spark.ml.clustering") setPredictionCol(String value)  
 * #### transform  
 public [Dataset](../../../../../org/apache/spark/sql/Dataset.html "class in org.apache.spark.sql")<[Row](../../../../../org/apache/spark/sql/Row.html "interface in org.apache.spark.sql")> transform([Dataset](../../../../../org/apache/spark/sql/Dataset.html "class in org.apache.spark.sql")<?> dataset)  
 Transforms the input dataset.  
 Specified by:  
 `[transform](../../../../../org/apache/spark/ml/Transformer.html#transform-org.apache.spark.sql.Dataset-)` in class `[Transformer](../../../../../org/apache/spark/ml/Transformer.html "class in org.apache.spark.ml")`  
 Parameters:  
 `dataset` \- (undocumented)  
 Returns:  
 (undocumented)  
 * #### transformSchema  
 public [StructType](../../../../../org/apache/spark/sql/types/StructType.html "class in org.apache.spark.sql.types") transformSchema([StructType](../../../../../org/apache/spark/sql/types/StructType.html "class in org.apache.spark.sql.types") schema)  
 Check transform validity and derive the output schema from the input schema.  
  We check validity for interactions between parameters during `transformSchema` and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by `Param.validate()`.  
  Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.  
 Specified by:  
 `[transformSchema](../../../../../org/apache/spark/ml/PipelineStage.html#transformSchema-org.apache.spark.sql.types.StructType-)` in class `[PipelineStage](../../../../../org/apache/spark/ml/PipelineStage.html "class in org.apache.spark.ml")`  
 Parameters:  
 `schema` \- (undocumented)  
 Returns:  
 (undocumented)  
 * #### predict  
 public int predict([Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg") features)  
 * #### clusterCenters  
 public [Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg")[] clusterCenters()  
 * #### write  
 public [GeneralMLWriter](../../../../../org/apache/spark/ml/util/GeneralMLWriter.html "class in org.apache.spark.ml.util") write()  
 Returns a [GeneralMLWriter](../../../../../org/apache/spark/ml/util/GeneralMLWriter.html "class in org.apache.spark.ml.util") instance for this ML instance.  
  For [KMeansModel](../../../../../org/apache/spark/ml/clustering/KMeansModel.html "class in org.apache.spark.ml.clustering"), this does NOT currently save the training `summary`. An option to save `summary` may be added in the future.  
 Specified by:  
 `[write](../../../../../org/apache/spark/ml/util/GeneralMLWritable.html#write--)` in interface `[GeneralMLWritable](../../../../../org/apache/spark/ml/util/GeneralMLWritable.html "interface in org.apache.spark.ml.util")`  
 Specified by:  
 `[write](../../../../../org/apache/spark/ml/util/MLWritable.html#write--)` in interface `[MLWritable](../../../../../org/apache/spark/ml/util/MLWritable.html "interface in org.apache.spark.ml.util")`  
 Returns:  
 (undocumented)  
 * #### toString  
 public String toString()  
 Specified by:  
 `[toString](../../../../../org/apache/spark/ml/util/Identifiable.html#toString--)` in interface `[Identifiable](../../../../../org/apache/spark/ml/util/Identifiable.html "interface in org.apache.spark.ml.util")`  
 Overrides:  
 `toString` in class `Object`  
 * #### summary  
 public [KMeansSummary](../../../../../org/apache/spark/ml/clustering/KMeansSummary.html "class in org.apache.spark.ml.clustering") summary()  
 Gets summary of model on training set. An exception is thrown if `hasSummary` is false.  
 Specified by:  
 `[summary](../../../../../org/apache/spark/ml/util/HasTrainingSummary.html#summary--)` in interface `[HasTrainingSummary](../../../../../org/apache/spark/ml/util/HasTrainingSummary.html "interface in org.apache.spark.ml.util")<[KMeansSummary](../../../../../org/apache/spark/ml/clustering/KMeansSummary.html "class in org.apache.spark.ml.clustering")>`  
 Returns:  
 (undocumented)

KMeansModel (Spark 3.5.5 JavaDoc) (original) (raw)

Nested Class Summary

Method Summary

Method Detail