Package | Description |
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ml.dmlc.xgboost4j.java |
Modifier and Type | Method and Description |
---|---|
DMatrix |
DMatrix.slice(int[] rowIndex)
Slice the DMatrix and return a new DMatrix that only contains `rowIndex`.
|
Modifier and Type | Method and Description |
---|---|
void |
Booster.boost(DMatrix dtrain,
float[] grad,
float[] hess)
update with give grad and hess
|
static String[] |
XGBoost.crossValidation(DMatrix data,
Map<String,Object> params,
int round,
int nfold,
String[] metrics,
IObjective obj,
IEvaluation eval)
Cross-validation with given parameters.
|
float |
IEvaluation.eval(float[][] predicts,
DMatrix dmat)
evaluate with predicts and data
|
String |
Booster.evalSet(DMatrix[] evalMatrixs,
String[] evalNames,
IEvaluation eval)
evaluate with given customized Evaluation class
|
String |
Booster.evalSet(DMatrix[] evalMatrixs,
String[] evalNames,
IEvaluation eval,
float[] metricsOut) |
String |
Booster.evalSet(DMatrix[] evalMatrixs,
String[] evalNames,
int iter)
evaluate with given dmatrixs.
|
String |
Booster.evalSet(DMatrix[] evalMatrixs,
String[] evalNames,
int iter,
float[] metricsOut)
evaluate with given dmatrixs.
|
List<float[]> |
IObjective.getGradient(float[][] predicts,
DMatrix dtrain)
user define objective function, return gradient and second order gradient
|
float[][] |
Booster.predict(DMatrix data)
Predict with data
|
float[][] |
Booster.predict(DMatrix data,
boolean outputMargin)
Predict with data
|
float[][] |
Booster.predict(DMatrix data,
boolean outputMargin,
int treeLimit)
Advanced predict function with all the options.
|
float[][] |
Booster.predictContrib(DMatrix data,
int treeLimit)
Output feature contributions toward predictions of given data
|
float[][] |
Booster.predictLeaf(DMatrix data,
int treeLimit)
Predict leaf indices given the data
|
static Booster |
XGBoost.train(DMatrix dtrain,
Map<String,Object> params,
int round,
Map<String,DMatrix> watches,
float[][] metrics,
IObjective obj,
IEvaluation eval,
int earlyStoppingRound)
Train a booster given parameters.
|
static Booster |
XGBoost.train(DMatrix dtrain,
Map<String,Object> params,
int round,
Map<String,DMatrix> watches,
float[][] metrics,
IObjective obj,
IEvaluation eval,
int earlyStoppingRounds,
Booster booster)
Train a booster given parameters.
|
static Booster |
XGBoost.train(DMatrix dtrain,
Map<String,Object> params,
int round,
Map<String,DMatrix> watches,
IObjective obj,
IEvaluation eval)
Train a booster given parameters.
|
static Booster |
XGBoost.trainAndSaveCheckpoint(DMatrix dtrain,
Map<String,Object> params,
int numRounds,
Map<String,DMatrix> watches,
float[][] metrics,
IObjective obj,
IEvaluation eval,
int earlyStoppingRounds,
Booster booster,
int checkpointInterval,
String checkpointPath,
org.apache.hadoop.fs.FileSystem fs) |
void |
Booster.update(DMatrix dtrain,
int iter)
Update the booster for one iteration.
|
void |
Booster.update(DMatrix dtrain,
IObjective obj)
Update with customize obj func
|
Modifier and Type | Method and Description |
---|---|
static Booster |
XGBoost.train(DMatrix dtrain,
Map<String,Object> params,
int round,
Map<String,DMatrix> watches,
float[][] metrics,
IObjective obj,
IEvaluation eval,
int earlyStoppingRound)
Train a booster given parameters.
|
static Booster |
XGBoost.train(DMatrix dtrain,
Map<String,Object> params,
int round,
Map<String,DMatrix> watches,
float[][] metrics,
IObjective obj,
IEvaluation eval,
int earlyStoppingRounds,
Booster booster)
Train a booster given parameters.
|
static Booster |
XGBoost.train(DMatrix dtrain,
Map<String,Object> params,
int round,
Map<String,DMatrix> watches,
IObjective obj,
IEvaluation eval)
Train a booster given parameters.
|
static Booster |
XGBoost.trainAndSaveCheckpoint(DMatrix dtrain,
Map<String,Object> params,
int numRounds,
Map<String,DMatrix> watches,
float[][] metrics,
IObjective obj,
IEvaluation eval,
int earlyStoppingRounds,
Booster booster,
int checkpointInterval,
String checkpointPath,
org.apache.hadoop.fs.FileSystem fs) |
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