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Spearman

Model API Type

Function API

ML API

def corr(dataset: Dataset[_], column: String, method: String): DataFrame

ML API

  • Function

    Import sample data in the dataset format, call the fitPredict API, and output the clustering result.

  • Input/Output
    1. Package name: org.apache.spark.ml.stat
    2. Class name: Correlation
    3. Method name: corr
    4. Input: training sample data (Dataset[_]). The following are mandatory fields.

      Parameter

      Type

      Description

      data

      Dataset[Vector]

      Matrix, which is stored in the unit of row

      column

      String

      Specifies columns for correlation matrix calculation.

      method

      String

      Correlation matrix method, which can be spearman
    5. Algorithm parameters

      Parameter

      Type

      Default Value

      Description

      method

      String

      pearson

      Method of solving the correlation matrix

      Code interface example:

      1
      val mat_df = ml.stat.Correlation.corr(data,"matrix", method = "spearman")
    6. Output: Pearson correlation matrix:

      Parameter

      Type

      Description

      df

      DataFrame

      Spearman matrix. The column name is column + method.
  • Sample usage
    val mat = stat.Correlation.corr(data, "matrix", "spearman")