Uses of Class
ml.dmlc.xgboost4j.java.XGBoostError

Packages that use XGBoostError

Package	Description
ml.dmlc.xgboost4j.java

Uses of XGBoostError in ml.dmlc.xgboost4j.java

Methods in ml.dmlc.xgboost4j.java that throw XGBoostError

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.
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.
String	Booster.getAttr(String key) Get attribute from the Booster.
Map<String,String>	Booster.getAttrs() Get attributes stored in the Booster as a Map.
float[]	DMatrix.getBaseMargin() Get base margin of the DMatrix.
Map<String,Integer>	Booster.getFeatureScore(String featureMap) Get importance of each feature
Map<String,Integer>	Booster.getFeatureScore(String[] featureNames) Get importance of each feature with specified feature names.
float[]	DMatrix.getLabel() get label values
String[]	Booster.getModelDump(String[] featureNames, boolean withStats) Get the dump of the model as a string array with specified feature names.
String[]	Booster.getModelDump(String[] featureNames, boolean withStats, String format)
String[]	Booster.getModelDump(String featureMap, boolean withStats) Get the dump of the model as a string array
String[]	Booster.getModelDump(String featureMap, boolean withStats, String format)
static int	Rabit.getRank() get rank of current thread.
Map<String,Double>	Booster.getScore(String[] featureNames, String importanceType) Get the feature importances for gain or cover (average or total)
Map<String,Double>	Booster.getScore(String featureMap, String importanceType) Get the feature importances for gain or cover (average or total), with feature names
float[]	DMatrix.getWeight() get weight of the DMatrix
static int	Rabit.getWorldSize() get world size of current job.
static void	Rabit.init(Map<String,String> envs) Initialize the rabit library on current working thread.
static Booster	XGBoost.loadModel(InputStream in) Load a new Booster model from a file opened as input stream.
static Booster	XGBoost.loadModel(String modelPath) load model from modelPath
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
long	DMatrix.rowNum() get the row number of DMatrix
void	Booster.saveModel(OutputStream out) Save the model to file opened as output stream.
void	Booster.saveModel(String modelPath) Save model to modelPath
void	Booster.setAttr(String key, String value) Set attribute to the Booster.
void	Booster.setAttrs(Map<String,String> attrs) Set attributes to the Booster.
void	DMatrix.setBaseMargin(float[] baseMargin) Set base margin (initial prediction).
void	DMatrix.setBaseMargin(float[][] baseMargin) Set base margin (initial prediction).
void	DMatrix.setGroup(int[] group) Set group sizes of DMatrix (used for ranking)
void	DMatrix.setLabel(float[] labels) set label of dmatrix
void	Booster.setParam(String key, Object value) Set parameter to the Booster.
void	Booster.setParams(Map<String,Object> params) Set parameters to the Booster.
void	DMatrix.setWeight(float[] weights) set weight of each instance
static void	Rabit.shutdown() Shutdown the rabit engine in current working thread, equals to finalize.
DMatrix	DMatrix.slice(int[] rowIndex) Slice the DMatrix and return a new DMatrix that only contains `rowIndex`.
byte[]	Booster.toByteArray()
static void	Rabit.trackerPrint(String msg) Print the message on rabit tracker.
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.
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
static int	Rabit.versionNumber() Get version number of current stored model in the thread.

Constructors in ml.dmlc.xgboost4j.java that throw XGBoostError

Constructor and Description
DMatrix(float[] data, int nrow, int ncol) create DMatrix from dense matrix
DMatrix(float[] data, int nrow, int ncol, float missing) create DMatrix from dense matrix
DMatrix(Iterator<LabeledPoint> iter, String cacheInfo) Create DMatrix from iterator.
DMatrix(long[] headers, int[] indices, float[] data, DMatrix.SparseType st) Deprecated.
DMatrix(long[] headers, int[] indices, float[] data, DMatrix.SparseType st, int shapeParam) Create DMatrix from Sparse matrix in CSR/CSC format.
DMatrix(String dataPath) Create DMatrix by loading libsvm file from dataPath
RabitTracker(int numWorkers)