org.apache.ignite.ml.composition.boosting.loss

## Interface Loss

- All Superinterfaces:
    Serializable
  All Known Implementing Classes:
    LogLoss, SquaredError

      public interface Loss
      extends Serializable

  Loss interface of computing error or gradient of error on specific row in dataset.

- - ### Method Summary

    All Methods Instance Methods Abstract Methods
    Modifier and Type | Method and Description
    --- | ---
    `double` | `error(long sampleSize, double lb, double mdlAnswer)` Error value for model answer.
    `double` | `gradient(long sampleSize, double lb, double mdlAnswer)` Error gradient value for model answer.

- - ### Method Detail

    - #### error

          double error(long sampleSize,
                       double lb,
                       double mdlAnswer)

      Error value for model answer.
      Parameters:
        `sampleSize` - Sample size.
        `lb` - Label.
        `mdlAnswer` - Model answer.
      Returns:
        Error value.

    - #### gradient

          double gradient(long sampleSize,
                          double lb,
                          double mdlAnswer)

      Error gradient value for model answer.
      Parameters:
        `sampleSize` - Sample size.
        `lb` - Label.
        `mdlAnswer` - Model answer.
      Returns:
        Error value.

2020 Copyright © Apache Software Foundation
| Follow @ApacheIgnite
Ignite Database and Caching Platform | : ver. 2.9.1
Release Date | : December 9 2020