biz.k11i.xgboost.gbm

Interface GradBooster

All Superinterfaces:

java.io.Serializable

All Known Implementing Classes:

Dart, GBLinear, GBTree

public interface GradBooster
extends java.io.Serializable

Interface of gradient boosting model.

Nested Class Summary

Nested Classes

Modifier and Type	Interface and Description
static class	GradBooster.Factory

Method Summary

Methods

Modifier and Type	Method and Description
void	loadModel(PredictorConfiguration config, ModelReader reader, boolean with_pbuffer) Loads model from stream.
float[]	predict(FVec feat, int ntree_limit, float base_score) Generates predictions for given feature vector.
int[]	predictLeaf(FVec feat, int ntree_limit) Predicts the leaf index of each tree.
java.lang.String[]	predictLeafPath(FVec feat, int ntree_limit) Predicts the path to leaf of each tree.
float	predictSingle(FVec feat, int ntree_limit, float base_score) Generates a prediction for given feature vector.
void	setNumClass(int numClass)
void	setNumFeature(int numFeature)

Method Detail

setNumClass

void setNumClass(int numClass)

setNumFeature

void setNumFeature(int numFeature)

loadModel

void loadModel(PredictorConfiguration config,
             ModelReader reader,
             boolean with_pbuffer)
               throws java.io.IOException

Loads model from stream.

Parameters:

config - predictor configuration

reader - input stream

with_pbuffer - whether the incoming data contains pbuffer

Throws:

java.io.IOException - If an I/O error occurs

predict

float[] predict(FVec feat,
              int ntree_limit,
              float base_score)

Generates predictions for given feature vector.

Parameters:

feat - feature vector

ntree_limit - limit the number of trees used in prediction

base_score - base score to initialize prediction

Returns:

prediction result

predictSingle

float predictSingle(FVec feat,
                  int ntree_limit,
                  float base_score)

Generates a prediction for given feature vector.

This method only works when the model outputs single value.

Parameters:

feat - feature vector

ntree_limit - limit the number of trees used in prediction

base_score - base score to initialize prediction

Returns:

prediction result

predictLeaf

int[] predictLeaf(FVec feat,
                int ntree_limit)

Predicts the leaf index of each tree. This is only valid in gbtree predictor.

Parameters:

feat - feature vector

ntree_limit - limit the number of trees used in prediction

Returns:

predicted leaf indexes

predictLeafPath

java.lang.String[] predictLeafPath(FVec feat,
                                 int ntree_limit)

Predicts the path to leaf of each tree. This is only valid in gbtree predictor.

Parameters:

feat - feature vector

ntree_limit - limit the number of trees used in prediction

Returns:

predicted path to leaves