org.tribuo.common.xgboost

Interface XGBoostOutputConverter<T extends Output<T>>

All Superinterfaces:

Serializable

All Known Implementing Classes:

XGBoostClassificationConverter, XGBoostRegressionConverter

public interface XGBoostOutputConverter<T extends Output<T>>
extends Serializable

Converts the output of XGBoost into the appropriate prediction type.

Method Summary

Modifier and Type	Method and Description
List<Prediction<T>>	convertBatchOutput(ImmutableOutputInfo<T> info, List<float[][]> probabilities, int[] numValidFeatures, Example<T>[] examples) Converts a list of float arrays from XGBoost Boosters into a Tribuo Prediction.
Prediction<T>	convertOutput(ImmutableOutputInfo<T> info, List<float[]> probabilities, int numValidFeatures, Example<T> example) Converts a list of float arrays from XGBoost Boosters into a Tribuo Prediction.
boolean	generatesProbabilities() Does this converter produce probabilities?

Method Detail

generatesProbabilities

boolean generatesProbabilities()

Does this converter produce probabilities?

Returns:

True if it produces probabilities.

convertOutput

Prediction<T> convertOutput(ImmutableOutputInfo<T> info,
                            List<float[]> probabilities,
                            int numValidFeatures,
                            Example<T> example)

Converts a list of float arrays from XGBoost Boosters into a Tribuo Prediction.

Parameters:

info - The output info.

probabilities - The XGBoost output.

numValidFeatures - The number of valid features used in the prediction.

example - The example this prediction was generated from.

Returns:

The prediction object.

convertBatchOutput

List<Prediction<T>> convertBatchOutput(ImmutableOutputInfo<T> info,
                                       List<float[][]> probabilities,
                                       int[] numValidFeatures,
                                       Example<T>[] examples)

Converts a list of float arrays from XGBoost Boosters into a Tribuo Prediction.

Parameters:

info - The output info.

probabilities - The XGBoost output, list dimension is across models, first array dimension is across examples, second array dimension is across outputs.

numValidFeatures - The number of valid features used in each prediction.

examples - The examples these predictions were generated from.

Returns:

The prediction object.