Value Members

1.  final def !=(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

2.  final def ##(): Int

   Definition Classes

   AnyRef → Any

3.  final def $[T](param: Param[T]): T

   An alias for getOrDefault().

   An alias for getOrDefault().

   Attributes

   protected

   Definition Classes

   Params

4.  final def ==(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

5.  final def asInstanceOf[T0]: T0

   Definition Classes

   Any

6.  final def clear(param: Param[_]): ClusteringEvaluator.this.type

   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

   Attributes

   protected[lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... ) @native()

8.  def copy(pMap: ParamMap): ClusteringEvaluator

   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

   ClusteringEvaluator → Evaluator → Params

   Annotations

   @Since( "2.3.0" )

9.  def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T

   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

    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.  val distanceMeasure: Param[String]

    param for distance measure to be used in evaluation (supports "squaredEuclidean" (default), "cosine")

    param for distance measure to be used in evaluation (supports "squaredEuclidean" (default), "cosine")

    Annotations

    @Since( "2.4.0" )

12.  final def eq(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

13.  def equals(arg0: Any): Boolean

    Definition Classes

    AnyRef → Any

14.  def evaluate(dataset: Dataset[_]): Double

    Evaluates model output and returns a scalar metric.

    Evaluates model output and returns a scalar metric. The value of isLargerBetter specifies whether larger values are better.

    dataset

    a dataset that contains labels/observations and predictions.

    returns

    metric

    Definition Classes

    ClusteringEvaluator → Evaluator

    Annotations

    @Since( "2.3.0" )

15.  def evaluate(dataset: Dataset[_], paramMap: ParamMap): Double

    Evaluates model output and returns a scalar metric.

    Evaluates model output and returns a scalar metric. The value of isLargerBetter specifies whether larger values are better.

    dataset

    a dataset that contains labels/observations and predictions.

    paramMap

    parameter map that specifies the input columns and output metrics

    returns

    metric

    Definition Classes

    Evaluator

    Annotations

    @Since( "2.0.0" )

16.  def explainParam(param: Param[_]): String

    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

17.  def explainParams(): String

    Explains all params of this instance.

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

    Definition Classes

    Params

18.  final def extractParamMap(): ParamMap

    extractParamMap with no extra values.

    extractParamMap with no extra values.

    Definition Classes

    Params

19.  final def extractParamMap(extra: ParamMap): ParamMap

    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

20.  final val featuresCol: Param[String]

    Param for features column name.

    Param for features column name.

    Definition Classes

    HasFeaturesCol

21.  def finalize(): Unit

    Attributes

    protected[lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

22.  final def get[T](param: Param[T]): Option[T]

    Optionally returns the user-supplied value of a param.

    Optionally returns the user-supplied value of a param.

    Definition Classes

    Params

23.  final def getClass(): Class[_]

    Definition Classes

    AnyRef → Any

    Annotations

    @native()

24.  final def getDefault[T](param: Param[T]): Option[T]

    Gets the default value of a parameter.

    Gets the default value of a parameter.

    Definition Classes

    Params

25.  def getDistanceMeasure: String
    Annotations

    @Since( "2.4.0" )

26.  final def getFeaturesCol: String
    Definition Classes

    HasFeaturesCol

27.  def getMetricName: String
    Annotations

    @Since( "2.3.0" )

28.  def getMetrics(dataset: Dataset[_]): ClusteringMetrics

    Get a ClusteringMetrics, which can be used to get clustering metrics such as silhouette score.

    Get a ClusteringMetrics, which can be used to get clustering metrics such as silhouette score.

    dataset

    a dataset that contains labels/observations and predictions.

    returns

    ClusteringMetrics

    Annotations

    @Since( "3.1.0" )

29.  final def getOrDefault[T](param: Param[T]): T

    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

30.  def getParam(paramName: String): Param[Any]

    Gets a param by its name.

    Gets a param by its name.

    Definition Classes

    Params

31.  final def getPredictionCol: String
    Definition Classes

    HasPredictionCol

32.  final def getWeightCol: String
    Definition Classes

    HasWeightCol

33.  final def hasDefault[T](param: Param[T]): Boolean

    Tests whether the input param has a default value set.

    Tests whether the input param has a default value set.

    Definition Classes

    Params

34.  def hasParam(paramName: String): Boolean

    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

35.  def hashCode(): Int

    Definition Classes

    AnyRef → Any

    Annotations

    @native()

36.  final def isDefined(param: Param[_]): Boolean

    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

37.  final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

38.  def isLargerBetter: Boolean

    Indicates whether the metric returned by evaluate should be maximized (true, default) or minimized (false).

    Indicates whether the metric returned by evaluate should be maximized (true, default) or minimized (false). A given evaluator may support multiple metrics which may be maximized or minimized.

    Definition Classes

    ClusteringEvaluator → Evaluator

    Annotations

    @Since( "2.3.0" )

39.  final def isSet(param: Param[_]): Boolean

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes

    Params

40.  val metricName: Param[String]

    param for metric name in evaluation (supports "silhouette" (default))

    param for metric name in evaluation (supports "silhouette" (default))

    Annotations

    @Since( "2.3.0" )

41.  final def ne(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

42.  final def notify(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

43.  final def notifyAll(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

44.  lazy val params: Array[Param[_]]

    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.

45.  final val predictionCol: Param[String]

    Param for prediction column name.

    Param for prediction column name.

    Definition Classes

    HasPredictionCol

46.  def save(path: String): Unit

    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( ... )

47.  final def set(paramPair: ParamPair[_]): ClusteringEvaluator.this.type

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Attributes

    protected

    Definition Classes

    Params

48.  final def set(param: String, value: Any): ClusteringEvaluator.this.type

    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

49.  final def set[T](param: Param[T], value: T): ClusteringEvaluator.this.type

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Definition Classes

    Params

50.  final def setDefault(paramPairs: ParamPair[_]*): ClusteringEvaluator.this.type

    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

51.  final def setDefault[T](param: Param[T], value: T): ClusteringEvaluator.this.type

    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[ml]

    Definition Classes

    Params

52.  def setDistanceMeasure(value: String): ClusteringEvaluator.this.type
    Annotations

    @Since( "2.4.0" )

53.  def setFeaturesCol(value: String): ClusteringEvaluator.this.type
    Annotations

    @Since( "2.3.0" )

54.  def setMetricName(value: String): ClusteringEvaluator.this.type
    Annotations

    @Since( "2.3.0" )

55.  def setPredictionCol(value: String): ClusteringEvaluator.this.type
    Annotations

    @Since( "2.3.0" )

56.  def setWeightCol(value: String): ClusteringEvaluator.this.type
    Annotations

    @Since( "3.1.0" )

57.  final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes

    AnyRef

58.  def toString(): String

    Definition Classes

    ClusteringEvaluator → Identifiable → AnyRef → Any

    Annotations

    @Since( "3.0.0" )

59.  val uid: String

    An immutable unique ID for the object and its derivatives.

    An immutable unique ID for the object and its derivatives.

    Definition Classes

    ClusteringEvaluator → Identifiable

    Annotations

    @Since( "2.3.0" )

60.  final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

61.  final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

62.  final def wait(arg0: Long): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... ) @native()

63.  final val weightCol: Param[String]

    Param for weight column name.

    Param for weight column name. If this is not set or empty, we treat all instance weights as 1.0.

    Definition Classes

    HasWeightCol

64.  def write: MLWriter

    Returns an MLWriter instance for this ML instance.

    Returns an MLWriter instance for this ML instance.

    Definition Classes

    DefaultParamsWritable → MLWritable