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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