Package org.apache.spark.ml.regression

Class GeneralizedLinearRegressionSummary

Object
org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
All Implemented Interfaces:
Serializable, Summary
Direct Known Subclasses:
GeneralizedLinearRegressionTrainingSummary
public class GeneralizedLinearRegressionSummary extends Object implements Summary, Serializable
Summary of GeneralizedLinearRegression model and predictions.

param: dataset Dataset to be summarized. param: origModel Model to be summarized. This is copied to create an internal model which cannot be modified from outside.

See Also:

  • Method Details

    • aic

      public double aic()

    • degreesOfFreedom

      public long degreesOfFreedom()

    • deviance

      public double deviance()

    • dispersion

      public double dispersion()

    • nullDeviance

      public double nullDeviance()

    • numInstances

      public long numInstances()

    • predictionCol

      public String predictionCol()
      Field in "predictions" which gives the predicted value of each instance. This is set to a new column name if the original model's predictionCol is not set.
      Returns:
      (undocumented)

    • predictions

      public Dataset<Row> predictions()
      Predictions output by the model's transform method.
      Returns:
      (undocumented)

    • rank

      public long rank()

    • residualDegreeOfFreedom

      public long residualDegreeOfFreedom()

    • residualDegreeOfFreedomNull

      public long residualDegreeOfFreedomNull()

    • residuals

      public Dataset<Row> residuals()
      Get the default residuals (deviance residuals) of the fitted model.
      Returns:
      (undocumented)

    • residuals

      public Dataset<Row> residuals(String residualsType)
      Get the residuals of the fitted model by type.

      Parameters:
      residualsType - The type of residuals which should be returned. Supported options: deviance, pearson, working and response.
      Returns:
      (undocumented)