org.apache.spark.mllib.api.python

PythonMLLibAPI

class PythonMLLibAPI extends Serializable

The Java stubs necessary for the Python mllib bindings.

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Instance Constructors

  1. new PythonMLLibAPI()

Value Members

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

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

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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

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  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 trainALSModel(ratingsBytesJRDD: JavaRDD[Array[Byte]], rank: Int, iterations: Int, lambda: Double, blocks: Int): MatrixFactorizationModel

    Java stub for Python mllib ALS.

    Java stub for Python mllib ALS.train(). This stub returns a handle to the Java object instead of the content of the Java object. Extra care needs to be taken in the Python code to ensure it gets freed on exit; see the Py4J documentation.

  20. def trainImplicitALSModel(ratingsBytesJRDD: JavaRDD[Array[Byte]], rank: Int, iterations: Int, lambda: Double, blocks: Int, alpha: Double): MatrixFactorizationModel

    Java stub for Python mllib ALS.

    Java stub for Python mllib ALS.trainImplicit(). This stub returns a handle to the Java object instead of the content of the Java object. Extra care needs to be taken in the Python code to ensure it gets freed on exit; see the Py4J documentation.

  21. def trainKMeansModel(dataBytesJRDD: JavaRDD[Array[Byte]], k: Int, maxIterations: Int, runs: Int, initializationMode: String): List[AnyRef]

    Java stub for Python mllib KMeans.

    Java stub for Python mllib KMeans.train()

  22. def trainLassoModelWithSGD(dataBytesJRDD: JavaRDD[Array[Byte]], numIterations: Int, stepSize: Double, regParam: Double, miniBatchFraction: Double, initialWeightsBA: Array[Byte]): List[AnyRef]

    Java stub for Python mllib LassoWithSGD.

    Java stub for Python mllib LassoWithSGD.train()

  23. def trainLinearRegressionModelWithSGD(dataBytesJRDD: JavaRDD[Array[Byte]], numIterations: Int, stepSize: Double, miniBatchFraction: Double, initialWeightsBA: Array[Byte]): List[AnyRef]

    Java stub for Python mllib LinearRegressionWithSGD.

    Java stub for Python mllib LinearRegressionWithSGD.train()

  24. def trainLogisticRegressionModelWithSGD(dataBytesJRDD: JavaRDD[Array[Byte]], numIterations: Int, stepSize: Double, miniBatchFraction: Double, initialWeightsBA: Array[Byte]): List[AnyRef]

    Java stub for Python mllib LogisticRegressionWithSGD.

    Java stub for Python mllib LogisticRegressionWithSGD.train()

  25. def trainNaiveBayes(dataBytesJRDD: JavaRDD[Array[Byte]], lambda: Double): List[AnyRef]

    Java stub for NaiveBayes.

    Java stub for NaiveBayes.train()

  26. def trainRidgeModelWithSGD(dataBytesJRDD: JavaRDD[Array[Byte]], numIterations: Int, stepSize: Double, regParam: Double, miniBatchFraction: Double, initialWeightsBA: Array[Byte]): List[AnyRef]

    Java stub for Python mllib RidgeRegressionWithSGD.

    Java stub for Python mllib RidgeRegressionWithSGD.train()

  27. def trainSVMModelWithSGD(dataBytesJRDD: JavaRDD[Array[Byte]], numIterations: Int, stepSize: Double, regParam: Double, miniBatchFraction: Double, initialWeightsBA: Array[Byte]): List[AnyRef]

    Java stub for Python mllib SVMWithSGD.

    Java stub for Python mllib SVMWithSGD.train()

  28. final def wait(): Unit

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

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

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