Package org.apache.spark.mllib.stat

Interface MultivariateStatisticalSummary

All Known Implementing Classes:
MultivariateOnlineSummarizer
public interface MultivariateStatisticalSummary
Trait for multivariate statistical summary of a data matrix.

  • Method Summary

    Modifier and Type
    Method
    Description
    long
    count()
    Sample size.
    Vector
    max()
    Maximum value of each column.
    Vector
    mean()
    Sample mean vector.
    Vector
    min()
    Minimum value of each column.
    Vector
    normL1()
    L1 norm of each column
    Vector
    normL2()
    Euclidean magnitude of each column
    Vector
    numNonzeros()
    Number of nonzero elements (including explicitly presented zero values) in each column.
    Vector
    variance()
    Sample variance vector.
    double
    weightSum()
    Sum of weights.

  • Method Details

    • count

      long count()
      Sample size.
      Returns:
      (undocumented)

    • max

      Vector max()
      Maximum value of each column.
      Returns:
      (undocumented)

    • mean

      Vector mean()
      Sample mean vector.
      Returns:
      (undocumented)

    • min

      Vector min()
      Minimum value of each column.
      Returns:
      (undocumented)

    • normL1

      Vector normL1()
      L1 norm of each column
      Returns:
      (undocumented)

    • normL2

      Vector normL2()
      Euclidean magnitude of each column
      Returns:
      (undocumented)

    • numNonzeros

      Vector numNonzeros()
      Number of nonzero elements (including explicitly presented zero values) in each column.
      Returns:
      (undocumented)

    • variance

      Vector variance()
      Sample variance vector. Should return a zero vector if the sample size is 1.
      Returns:
      (undocumented)

    • weightSum

      double weightSum()
      Sum of weights.
      Returns:
      (undocumented)