object KMeans extends Serializable
Top-level methods for calling K-means clustering.
- Annotations
- @Since("0.8.0")
- Source
- KMeans.scala
- Alphabetic
- By Inheritance
- KMeans
- Serializable
- AnyRef
- Any
- Hide All
- Show All
- Public
- Protected
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- val K_MEANS_PARALLEL: String
- Annotations
- @Since("0.8.0")
- val RANDOM: String
- Annotations
- @Since("0.8.0")
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @IntrinsicCandidate() @native()
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @IntrinsicCandidate() @native()
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @IntrinsicCandidate() @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @IntrinsicCandidate() @native()
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- AnyRef → Any
- def train(data: RDD[Vector], k: Int, maxIterations: Int): KMeansModel
Trains a k-means model using specified parameters and the default values for unspecified.
Trains a k-means model using specified parameters and the default values for unspecified.
- Annotations
- @Since("0.8.0")
- def train(data: RDD[Vector], k: Int, maxIterations: Int, initializationMode: String): KMeansModel
Trains a k-means model using the given set of parameters.
Trains a k-means model using the given set of parameters.
- data
Training points as an
RDD
ofVector
types.- k
Number of clusters to create.
- maxIterations
Maximum number of iterations allowed.
- initializationMode
The initialization algorithm. This can either be "random" or "k-means||". (default: "k-means||")
- Annotations
- @Since("2.1.0")
- def train(data: RDD[Vector], k: Int, maxIterations: Int, initializationMode: String, seed: Long): KMeansModel
Trains a k-means model using the given set of parameters.
Trains a k-means model using the given set of parameters.
- data
Training points as an
RDD
ofVector
types.- k
Number of clusters to create.
- maxIterations
Maximum number of iterations allowed.
- initializationMode
The initialization algorithm. This can either be "random" or "k-means||". (default: "k-means||")
- seed
Random seed for cluster initialization. Default is to generate seed based on system time.
- Annotations
- @Since("2.1.0")
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
Deprecated Value Members
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated
(Since version 9)