class BisectingKMeansModel extends Serializable with Saveable with Logging
Clustering model produced by BisectingKMeans. The prediction is done level-by-level from the root node to a leaf node, and at each node among its children the closest to the input point is selected.
- Annotations
- @Since("1.6.0")
- Source
- BisectingKMeansModel.scala
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Instance Constructors
- new BisectingKMeansModel(root: ClusteringTreeNode)
- Annotations
- @Since("1.6.0")
Type Members
- implicit class LogStringContext extends AnyRef
- Definition Classes
- Logging
Value Members
- final def !=(arg0: Any): Boolean
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- final def ##: Int
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- final def ==(arg0: Any): Boolean
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- def MDC(key: LogKey, value: Any): MDC
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- @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
- def clusterCenters: Array[Vector]
Leaf cluster centers.
Leaf cluster centers.
- Annotations
- @Since("1.6.0")
- def computeCost(data: JavaRDD[Vector]): Double
Java-friendly version of
computeCost().Java-friendly version of
computeCost().- Annotations
- @Since("1.6.0")
- def computeCost(data: RDD[Vector]): Double
Computes the sum of squared distances between the input points and their corresponding cluster centers.
Computes the sum of squared distances between the input points and their corresponding cluster centers.
- Annotations
- @Since("1.6.0")
- def computeCost(point: Vector): Double
Computes the squared distance between the input point and the cluster center it belongs to.
Computes the squared distance between the input point and the cluster center it belongs to.
- Annotations
- @Since("1.6.0")
- val distanceMeasure: String
- Annotations
- @Since("2.4.0")
- final def eq(arg0: AnyRef): Boolean
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- def hashCode(): Int
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- @IntrinsicCandidate() @native()
- def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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- Logging
- def initializeLogIfNecessary(isInterpreter: Boolean): Unit
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- final def isInstanceOf[T0]: Boolean
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- def isTraceEnabled(): Boolean
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- Logging
- lazy val k: Int
Number of leaf clusters.
- def log: Logger
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- Logging
- def logBasedOnLevel(level: Level)(f: => MessageWithContext): Unit
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- def logDebug(msg: => String, throwable: Throwable): Unit
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- def logDebug(entry: LogEntry, throwable: Throwable): Unit
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- def logDebug(entry: LogEntry): Unit
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- def logDebug(msg: => String): Unit
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- def logError(msg: => String, throwable: Throwable): Unit
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- def logError(entry: LogEntry, throwable: Throwable): Unit
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- def logError(entry: LogEntry): Unit
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- def logError(msg: => String): Unit
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- def logInfo(msg: => String, throwable: Throwable): Unit
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- def logInfo(entry: LogEntry, throwable: Throwable): Unit
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- def logInfo(entry: LogEntry): Unit
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- Logging
- def logInfo(msg: => String): Unit
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- def logName: String
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- Logging
- def logTrace(msg: => String, throwable: Throwable): Unit
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- Logging
- def logTrace(entry: LogEntry, throwable: Throwable): Unit
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- def logTrace(entry: LogEntry): Unit
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- Logging
- def logTrace(msg: => String): Unit
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- def logWarning(msg: => String, throwable: Throwable): Unit
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- def logWarning(entry: LogEntry, throwable: Throwable): Unit
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- def logWarning(entry: LogEntry): Unit
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- def logWarning(msg: => String): Unit
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- final def ne(arg0: AnyRef): Boolean
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- final def notify(): Unit
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- @IntrinsicCandidate() @native()
- final def notifyAll(): Unit
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- @IntrinsicCandidate() @native()
- def predict(points: JavaRDD[Vector]): JavaRDD[Integer]
Java-friendly version of
predict().Java-friendly version of
predict().- Annotations
- @Since("1.6.0")
- def predict(points: RDD[Vector]): RDD[Int]
Predicts the indices of the clusters that the input points belong to.
Predicts the indices of the clusters that the input points belong to.
- Annotations
- @Since("1.6.0")
- def predict(point: Vector): Int
Predicts the index of the cluster that the input point belongs to.
Predicts the index of the cluster that the input point belongs to.
- Annotations
- @Since("1.6.0")
- def save(sc: SparkContext, path: String): Unit
Save this model to the given path.
Save this model to the given path.
This saves:
- human-readable (JSON) model metadata to path/metadata/
- Parquet formatted data to path/data/
The model may be loaded using
Loader.load.- sc
Spark context used to save model data.
- path
Path specifying the directory in which to save this model. If the directory already exists, this method throws an exception.
- Definition Classes
- BisectingKMeansModel → Saveable
- Annotations
- @Since("2.0.0")
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- AnyRef → Any
- val trainingCost: Double
- Annotations
- @Since("3.0.0")
- final def wait(arg0: Long, arg1: Int): Unit
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- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
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- final def wait(): Unit
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- def withLogContext(context: Map[String, String])(body: => Unit): Unit
- Attributes
- protected
- Definition Classes
- Logging
Deprecated Value Members
- def finalize(): Unit
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- protected[lang]
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- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated
(Since version 9)