com.github.cloudml.zen.ml.recommendation

BSFM

object BSFM extends Serializable

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

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  15. final def notify(): 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 trainClassification(input: RDD[(Long, LabeledPoint)], numIterations: Int, stepSize: Double, views: Array[Long], l2: (Double, Double, Double), rank: Int, useAdaGrad: Boolean = true, miniBatchFraction: Double = 1.0, storageLevel: StorageLevel = StorageLevel.MEMORY_AND_DISK): BSFMModel

    BS-FM clustering

    BS-FM clustering

    input

    train data

    numIterations
    stepSize

    recommend 1e-2- 1e-1

    views

    特征视图

    l2

    (w_0, w_i, v_{i,f}) in L2 regularization

    rank

    recommend 10-20

    useAdaGrad

    use AdaGrad to train

    miniBatchFraction
    storageLevel
    returns

  20. def trainRegression(input: RDD[(Long, LabeledPoint)], numIterations: Int, stepSize: Double, views: Array[Long], l2: (Double, Double, Double), rank: Int, useAdaGrad: Boolean = true, miniBatchFraction: Double = 1.0, storageLevel: StorageLevel = StorageLevel.MEMORY_AND_DISK): BSFMModel

    BS-FM regression

    BS-FM regression

    input

    train data

    numIterations
    stepSize

    recommend 1e-2- 1e-1

    l2

    (w_0, w_i, v_{i,f}) in L2 regularization

    rank

    recommend 10-20

    useAdaGrad

    use AdaGrad to train

    miniBatchFraction
    storageLevel
    returns

  21. final def wait(): Unit

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

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

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