biz.k11i.xgboost.gbm

Class GBLinear

java.lang.Object

biz.k11i.xgboost.gbm.GBLinear

All Implemented Interfaces:

GradBooster, java.io.Serializable

public class GBLinear
extends java.lang.Object

Linear booster implementation

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface biz.k11i.xgboost.gbm.GradBooster

GradBooster.Factory

Field Summary

Fields

Modifier and Type	Field and Description
protected int	num_class
protected int	num_feature
protected int	num_output_group

Constructor Summary

Constructors

Constructor and Description
GBLinear()

Method Summary

Methods

Modifier and Type	Method and Description
float	bias(int gid)
int	getNumFeature()
int	getNumOutputGroup()
void	loadModel(PredictorConfiguration config, ModelReader reader, boolean ignored_with_pbuffer) Loads model from stream.
float[]	predict(FVec feat, int ntree_limit) 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) Generates a prediction for given feature vector.
void	setNumClass(int numClass)
void	setNumFeature(int numFeature)
float	weight(int fid, int gid)

Methods inherited from class java.lang.Object

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

Field Detail

num_class

protected int num_class

num_feature

protected int num_feature

num_output_group

protected int num_output_group

Constructor Detail

GBLinear

public GBLinear()

Method Detail

loadModel

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

Description copied from interface: GradBooster

Loads model from stream.

Parameters:

config - predictor configuration

reader - input stream

ignored_with_pbuffer - whether the incoming data contains pbuffer

Throws:

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

predict

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

Description copied from interface: GradBooster

Generates predictions for given feature vector.

Parameters:

feat - feature vector

ntree_limit - limit the number of trees used in prediction

Returns:

prediction result

predictSingle

public float predictSingle(FVec feat,
                  int ntree_limit)

Description copied from interface: GradBooster

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

Returns:

prediction result

predictLeaf

public int[] predictLeaf(FVec feat,
                int ntree_limit)

Description copied from interface: GradBooster

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

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

Description copied from interface: GradBooster

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

weight

public float weight(int fid,
           int gid)

bias

public float bias(int gid)

getNumFeature

public int getNumFeature()

getNumOutputGroup

public int getNumOutputGroup()

setNumClass

public void setNumClass(int numClass)

Specified by:

setNumClass in interface GradBooster

setNumFeature

public void setNumFeature(int numFeature)

Specified by:

setNumFeature in interface GradBooster