Class/Object

org.apache.spark.ml.clustering

KMeans

Related Docs: object KMeans | package clustering

Permalink

class KMeans extends Estimator[KMeansModel] with KMeansParams with DefaultParamsWritable

K-means clustering with support for k-means|| initialization proposed by Bahmani et al.

Annotations
@Since( "1.5.0" )
Source
KMeans.scala
See also

Bahmani et al., Scalable k-means++.

Linear Supertypes
Ordering
  1. Grouped
  2. Alphabetic
  3. By Inheritance
Inherited
  1. KMeans
  2. DefaultParamsWritable
  3. MLWritable
  4. KMeansParams
  5. HasDistanceMeasure
  6. HasTol
  7. HasPredictionCol
  8. HasSeed
  9. HasFeaturesCol
  10. HasMaxIter
  11. Estimator
  12. PipelineStage
  13. Logging
  14. Params
  15. Serializable
  16. Serializable
  17. Identifiable
  18. AnyRef
  19. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new KMeans()

    Permalink
    Annotations
    @Since( "1.5.0" )
  2. new KMeans(uid: String)

    Permalink
    Annotations
    @Since( "1.5.0" )

Value Members

  1. final def !=(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T

    Permalink

    An alias for getOrDefault().

    An alias for getOrDefault().

    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any
  6. final def clear(param: Param[_]): KMeans.this.type

    Permalink

    Clears the user-supplied value for the input param.

    Clears the user-supplied value for the input param.

    Definition Classes
    Params
  7. def clone(): AnyRef

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. def copy(extra: ParamMap): KMeans

    Permalink

    Creates a copy of this instance with the same UID and some extra params.

    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().

    Definition Classes
    KMeansEstimatorPipelineStageParams
    Annotations
    @Since( "1.5.0" )
  9. def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T

    Permalink

    Copies param values from this instance to another instance for params shared by them.

    Copies param values from this instance to another instance for params shared by them.

    This handles default Params and explicitly set Params separately. Default Params are copied from and to defaultParamMap, and explicitly set Params are copied from and to paramMap. Warning: This implicitly assumes that this Params instance and the target instance share the same set of default Params.

    to

    the target instance, which should work with the same set of default Params as this source instance

    extra

    extra params to be copied to the target's paramMap

    returns

    the target instance with param values copied

    Attributes
    protected
    Definition Classes
    Params
  10. final def defaultCopy[T <: Params](extra: ParamMap): T

    Permalink

    Default implementation of copy with extra params.

    Default implementation of copy with extra params. It tries to create a new instance with the same UID. Then it copies the embedded and extra parameters over and returns the new instance.

    Attributes
    protected
    Definition Classes
    Params
  11. final val distanceMeasure: Param[String]

    Permalink

    Param for The distance measure.

    Param for The distance measure. Supported options: 'euclidean' and 'cosine'.

    Definition Classes
    HasDistanceMeasure
  12. final def eq(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  13. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  14. def explainParam(param: Param[_]): String

    Permalink

    Explains a param.

    Explains a param.

    param

    input param, must belong to this instance.

    returns

    a string that contains the input param name, doc, and optionally its default value and the user-supplied value

    Definition Classes
    Params
  15. def explainParams(): String

    Permalink

    Explains all params of this instance.

    Explains all params of this instance. See explainParam().

    Definition Classes
    Params
  16. final def extractParamMap(): ParamMap

    Permalink

    extractParamMap with no extra values.

    extractParamMap with no extra values.

    Definition Classes
    Params
  17. final def extractParamMap(extra: ParamMap): ParamMap

    Permalink

    Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.

    Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.

    Definition Classes
    Params
  18. final val featuresCol: Param[String]

    Permalink

    Param for features column name.

    Param for features column name.

    Definition Classes
    HasFeaturesCol
  19. def finalize(): Unit

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  20. def fit(dataset: Dataset[_]): KMeansModel

    Permalink

    Fits a model to the input data.

    Fits a model to the input data.

    Definition Classes
    KMeansEstimator
    Annotations
    @Since( "2.0.0" )
  21. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[KMeansModel]

    Permalink

    Fits multiple models to the input data with multiple sets of parameters.

    Fits multiple models to the input data with multiple sets of parameters. The default implementation uses a for loop on each parameter map. Subclasses could override this to optimize multi-model training.

    dataset

    input dataset

    paramMaps

    An array of parameter maps. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted models, matching the input parameter maps

    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  22. def fit(dataset: Dataset[_], paramMap: ParamMap): KMeansModel

    Permalink

    Fits a single model to the input data with provided parameter map.

    Fits a single model to the input data with provided parameter map.

    dataset

    input dataset

    paramMap

    Parameter map. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  23. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): KMeansModel

    Permalink

    Fits a single model to the input data with optional parameters.

    Fits a single model to the input data with optional parameters.

    dataset

    input dataset

    firstParamPair

    the first param pair, overrides embedded params

    otherParamPairs

    other param pairs. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  24. final def get[T](param: Param[T]): Option[T]

    Permalink

    Optionally returns the user-supplied value of a param.

    Optionally returns the user-supplied value of a param.

    Definition Classes
    Params
  25. final def getClass(): Class[_]

    Permalink
    Definition Classes
    AnyRef → Any
  26. final def getDefault[T](param: Param[T]): Option[T]

    Permalink

    Gets the default value of a parameter.

    Gets the default value of a parameter.

    Definition Classes
    Params
  27. final def getDistanceMeasure: String

    Permalink

    Definition Classes
    HasDistanceMeasure
  28. final def getFeaturesCol: String

    Permalink

    Definition Classes
    HasFeaturesCol
  29. def getInitMode: String

    Permalink

    Definition Classes
    KMeansParams
    Annotations
    @Since( "1.5.0" )
  30. def getInitSteps: Int

    Permalink

    Definition Classes
    KMeansParams
    Annotations
    @Since( "1.5.0" )
  31. def getK: Int

    Permalink

    Definition Classes
    KMeansParams
    Annotations
    @Since( "1.5.0" )
  32. final def getMaxIter: Int

    Permalink

    Definition Classes
    HasMaxIter
  33. final def getOrDefault[T](param: Param[T]): T

    Permalink

    Gets the value of a param in the embedded param map or its default value.

    Gets the value of a param in the embedded param map or its default value. Throws an exception if neither is set.

    Definition Classes
    Params
  34. def getParam(paramName: String): Param[Any]

    Permalink

    Gets a param by its name.

    Gets a param by its name.

    Definition Classes
    Params
  35. final def getPredictionCol: String

    Permalink

    Definition Classes
    HasPredictionCol
  36. final def getSeed: Long

    Permalink

    Definition Classes
    HasSeed
  37. final def getTol: Double

    Permalink

    Definition Classes
    HasTol
  38. final def hasDefault[T](param: Param[T]): Boolean

    Permalink

    Tests whether the input param has a default value set.

    Tests whether the input param has a default value set.

    Definition Classes
    Params
  39. def hasParam(paramName: String): Boolean

    Permalink

    Tests whether this instance contains a param with a given name.

    Tests whether this instance contains a param with a given name.

    Definition Classes
    Params
  40. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  41. final val initMode: Param[String]

    Permalink

    Param for the initialization algorithm.

    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||.

    Definition Classes
    KMeansParams
    Annotations
    @Since( "1.5.0" )
  42. final val initSteps: IntParam

    Permalink

    Param for the number of steps for the k-means|| initialization mode.

    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 > 0. Default: 2.

    Definition Classes
    KMeansParams
    Annotations
    @Since( "1.5.0" )
  43. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean = false): Boolean

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  44. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  45. final def isDefined(param: Param[_]): Boolean

    Permalink

    Checks whether a param is explicitly set or has a default value.

    Checks whether a param is explicitly set or has a default value.

    Definition Classes
    Params
  46. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any
  47. final def isSet(param: Param[_]): Boolean

    Permalink

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  48. def isTraceEnabled(): Boolean

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  49. final val k: IntParam

    Permalink

    The number of clusters to create (k).

    The number of clusters to create (k). Must be > 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.

    Definition Classes
    KMeansParams
    Annotations
    @Since( "1.5.0" )
  50. def log: Logger

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  51. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  52. def logDebug(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  53. def logError(msg: ⇒ String, throwable: Throwable): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  54. def logError(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  55. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  56. def logInfo(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  57. def logName: String

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  58. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  59. def logTrace(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  60. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  61. def logWarning(msg: ⇒ String): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    Logging
  62. final val maxIter: IntParam

    Permalink

    Param for maximum number of iterations (>= 0).

    Param for maximum number of iterations (>= 0).

    Definition Classes
    HasMaxIter
  63. final def ne(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  64. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef
  65. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef
  66. lazy val params: Array[Param[_]]

    Permalink

    Returns all params sorted by their names.

    Returns all params sorted by their names. The default implementation uses Java reflection to list all public methods that have no arguments and return Param.

    Definition Classes
    Params
    Note

    Developer should not use this method in constructor because we cannot guarantee that this variable gets initialized before other params.

  67. final val predictionCol: Param[String]

    Permalink

    Param for prediction column name.

    Param for prediction column name.

    Definition Classes
    HasPredictionCol
  68. def save(path: String): Unit

    Permalink

    Saves this ML instance to the input path, a shortcut of write.save(path).

    Saves this ML instance to the input path, a shortcut of write.save(path).

    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  69. final val seed: LongParam

    Permalink

    Param for random seed.

    Param for random seed.

    Definition Classes
    HasSeed
  70. final def set(paramPair: ParamPair[_]): KMeans.this.type

    Permalink

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Attributes
    protected
    Definition Classes
    Params
  71. final def set(param: String, value: Any): KMeans.this.type

    Permalink

    Sets a parameter (by name) in the embedded param map.

    Sets a parameter (by name) in the embedded param map.

    Attributes
    protected
    Definition Classes
    Params
  72. final def set[T](param: Param[T], value: T): KMeans.this.type

    Permalink

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Definition Classes
    Params
  73. final def setDefault(paramPairs: ParamPair[_]*): KMeans.this.type

    Permalink

    Sets default values for a list of params.

    Sets default values for a list of params.

    Note: Java developers should use the single-parameter setDefault. Annotating this with varargs can cause compilation failures due to a Scala compiler bug. See SPARK-9268.

    paramPairs

    a list of param pairs that specify params and their default values to set respectively. Make sure that the params are initialized before this method gets called.

    Attributes
    protected
    Definition Classes
    Params
  74. final def setDefault[T](param: Param[T], value: T): KMeans.this.type

    Permalink

    Sets a default value for a param.

    Sets a default value for a param.

    param

    param to set the default value. Make sure that this param is initialized before this method gets called.

    value

    the default value

    Attributes
    protected
    Definition Classes
    Params
  75. def setDistanceMeasure(value: String): KMeans.this.type

    Permalink

    Annotations
    @Since( "2.4.0" )
  76. def setFeaturesCol(value: String): KMeans.this.type

    Permalink

    Annotations
    @Since( "1.5.0" )
  77. def setInitMode(value: String): KMeans.this.type

    Permalink

    Annotations
    @Since( "1.5.0" )
  78. def setInitSteps(value: Int): KMeans.this.type

    Permalink

    Annotations
    @Since( "1.5.0" )
  79. def setK(value: Int): KMeans.this.type

    Permalink

    Annotations
    @Since( "1.5.0" )
  80. def setMaxIter(value: Int): KMeans.this.type

    Permalink

    Annotations
    @Since( "1.5.0" )
  81. def setPredictionCol(value: String): KMeans.this.type

    Permalink

    Annotations
    @Since( "1.5.0" )
  82. def setSeed(value: Long): KMeans.this.type

    Permalink

    Annotations
    @Since( "1.5.0" )
  83. def setTol(value: Double): KMeans.this.type

    Permalink

    Annotations
    @Since( "1.5.0" )
  84. final def synchronized[T0](arg0: ⇒ T0): T0

    Permalink
    Definition Classes
    AnyRef
  85. def toString(): String

    Permalink
    Definition Classes
    Identifiable → AnyRef → Any
  86. final val tol: DoubleParam

    Permalink

    Param for the convergence tolerance for iterative algorithms (>= 0).

    Param for the convergence tolerance for iterative algorithms (>= 0).

    Definition Classes
    HasTol
  87. def transformSchema(schema: StructType): StructType

    Permalink

    :: DeveloperApi ::

    :: DeveloperApi ::

    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.

    Definition Classes
    KMeansPipelineStage
    Annotations
    @Since( "1.5.0" )
  88. def transformSchema(schema: StructType, logging: Boolean): StructType

    Permalink

    :: DeveloperApi ::

    :: DeveloperApi ::

    Derives the output schema from the input schema and parameters, optionally with logging.

    This should be optimistic. If it is unclear whether the schema will be valid, then it should be assumed valid until proven otherwise.

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  89. val uid: String

    Permalink

    An immutable unique ID for the object and its derivatives.

    An immutable unique ID for the object and its derivatives.

    Definition Classes
    KMeansIdentifiable
    Annotations
    @Since( "1.5.0" )
  90. def validateAndTransformSchema(schema: StructType): StructType

    Permalink

    Validates and transforms the input schema.

    Validates and transforms the input schema.

    schema

    input schema

    returns

    output schema

    Attributes
    protected
    Definition Classes
    KMeansParams
  91. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  92. final def wait(arg0: Long, arg1: Int): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  93. final def wait(arg0: Long): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  94. def write: MLWriter

    Permalink

    Returns an MLWriter instance for this ML instance.

    Returns an MLWriter instance for this ML instance.

    Definition Classes
    DefaultParamsWritableMLWritable

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from KMeansParams

Inherited from HasDistanceMeasure

Inherited from HasTol

Inherited from HasPredictionCol

Inherited from HasSeed

Inherited from HasFeaturesCol

Inherited from HasMaxIter

Inherited from Estimator[KMeansModel]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

A list of (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.

Members

Parameter setters

Parameter getters

(expert-only) Parameters

A list of advanced, expert-only (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.

(expert-only) Parameter setters

(expert-only) Parameter getters