Package org.apache.spark.mllib.tree.loss

Class SquaredError

Object
org.apache.spark.mllib.tree.loss.SquaredError
public class SquaredError extends Object
Class for squared error loss calculation.

The squared (L2) error is defined as: (y - F(x))**2 where y is the label and F(x) is the model prediction for features x.

  • Constructor Summary

    Constructors
    Constructor
    Description
    SquaredError()
     

  • Method Summary

    Modifier and Type
    Method
    Description
    static double
    gradient(double prediction, double label)
    Method to calculate the gradients for the gradient boosting calculation for least squares error calculation.

    Methods inherited from class java.lang.Object

    equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

  • Constructor Details

    • SquaredError

      public SquaredError()

  • Method Details

    • gradient

      public static double gradient(double prediction, double label)
      Method to calculate the gradients for the gradient boosting calculation for least squares error calculation. The gradient with respect to F(x) is: - 2 (y - F(x))
      Parameters:
      prediction - Predicted label.
      label - True label.
      Returns:
      Loss gradient