KMeans

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

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. val K_MEANS_PARALLEL: String

   

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   @Since( "0.8.0" )

5. val RANDOM: String

   

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   @Since( "0.8.0" )

6. final def asInstanceOf[T0]: T0

   

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7. def clone(): AnyRef

   

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8. final def eq(arg0: AnyRef): Boolean

   

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9. def equals(arg0: Any): Boolean

   

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10. def finalize(): Unit

    

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11. final def getClass(): Class[_]

    

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12. def hashCode(): Int

    

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13. final def isInstanceOf[T0]: Boolean

    

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14. final def ne(arg0: AnyRef): Boolean

    

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15. final def notify(): Unit

    

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16. final def notifyAll(): Unit

    

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

    

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18. def toString(): String

    

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19. def train(data: RDD[Vector], k: Int, maxIterations: Int, runs: 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.

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    @Since( "0.8.0" )

20. 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.

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    @Since( "0.8.0" )

21. def train(data: RDD[Vector], k: Int, maxIterations: Int, runs: 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 of Vector types.

    k

    Number of clusters to create.

    maxIterations

    Maximum number of iterations allowed.

    runs

    This param has no effect since Spark 2.0.0.

    initializationMode

    The initialization algorithm. This can either be "random" or "k-means||". (default: "k-means||")

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    @Since( "0.8.0" )

22. def train(data: RDD[Vector], k: Int, maxIterations: Int, runs: 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 of Vector types.

    k

    Number of clusters to create.

    maxIterations

    Maximum number of iterations allowed.

    runs

    This param has no effect since Spark 2.0.0.

    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.

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    @Since( "1.3.0" )

23. final def wait(): Unit

    

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

    

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25. final def wait(arg0: Long): Unit

    

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