MLUtils

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. def computeStats(data: RDD[LabeledPoint], nfeatures: Int, nexamples: Long): (Double, DoubleMatrix, DoubleMatrix)

   Utility function to compute mean and standard deviation on a given dataset.

   Utility function to compute mean and standard deviation on a given dataset.

   data

   - input data set whose statistics are computed

   nfeatures

   - number of features

   nexamples

   - number of examples in input dataset

   returns

   (yMean, xColMean, xColSd) - Tuple consisting of yMean - mean of the labels xColMean - Row vector with mean for every column (or feature) of the input data xColSd - Row vector standard deviation for every column (or feature) of the input data.

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

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10. def equals(arg0: Any): Boolean

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11. def finalize(): Unit

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

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13. def hashCode(): Int

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14. final def isInstanceOf[T0]: Boolean

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15. def loadLabeledData(sc: SparkContext, dir: String): RDD[LabeledPoint]

    Load labeled data from a file.

    Load labeled data from a file. The data format used here is <L>, <f1> <f2> ... where <f1>, <f2> are feature values in Double and <L> is the corresponding label as Double.

    sc

    SparkContext

    dir

    Directory to the input data files.

    returns

    An RDD of LabeledPoint. Each labeled point has two elements: the first element is the label, and the second element represents the feature values (an array of Double).

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

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17. final def notify(): Unit

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18. final def notifyAll(): Unit

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19. def saveLabeledData(data: RDD[LabeledPoint], dir: String): Unit

    Save labeled data to a file.

    Save labeled data to a file. The data format used here is <L>, <f1> <f2> ... where <f1>, <f2> are feature values in Double and <L> is the corresponding label as Double.

    data

    An RDD of LabeledPoints containing data to be saved.

    dir

    Directory to save the data.

20. def squaredDistance(v1: Array[Double], v2: Array[Double]): Double

    Return the squared Euclidean distance between two vectors.

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

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22. def toString(): String

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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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