## 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.
    `int[]` | DMatrix.`getGroup()` Get group sizes of DMatrix
    `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)`
    `long` | Booster.`getNumFeature()` Get number of model features.
    `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.
    `Booster` | ExternalCheckpointManager.`loadCheckpointAsBooster()`
    `static Booster` | XGBoost.`loadModel(byte[] buffer)` Load a new Booster model from a byte array buffer.
    `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` | DeviceQuantileDMatrix.`setBaseMargin(Column column)`
    `void` | DMatrix.`setBaseMargin(Column column)` Set base margin of DMatrix from cuda array interface
    `void` | DeviceQuantileDMatrix.`setBaseMargin(float[] baseMargin)`
    `void` | DMatrix.`setBaseMargin(float[] baseMargin)` Set base margin (initial prediction).
    `void` | DeviceQuantileDMatrix.`setBaseMargin(float[][] baseMargin)`
    `void` | DMatrix.`setBaseMargin(float[][] baseMargin)` Set base margin (initial prediction).
    `void` | DeviceQuantileDMatrix.`setGroup(int[] group)`
    `void` | DMatrix.`setGroup(int[] group)` Set group sizes of DMatrix (used for ranking)
    `void` | DeviceQuantileDMatrix.`setLabel(Column column)`
    `void` | DMatrix.`setLabel(Column column)` Set label of DMatrix from cuda array interface
    `void` | DeviceQuantileDMatrix.`setLabel(float[] labels)`
    `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` | DeviceQuantileDMatrix.`setWeight(Column column)`
    `void` | DMatrix.`setWeight(Column column)` Set weight of DMatrix from cuda array interface
    `void` | DeviceQuantileDMatrix.`setWeight(float[] weights)`
    `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()` Save model into raw byte array.
    `byte[]` | Booster.`toByteArray(String format)` Save model into raw byte array.
    `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.
    `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
    `void` | ExternalCheckpointManager.`updateCheckpoint(Booster boosterToCheckpoint)`
    `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
    `DeviceQuantileDMatrix(Iterator<ColumnBatch> iter, float missing, int maxBin, int nthread)` Create DeviceQuantileDMatrix from iterator based on the cuda array interface
    `DMatrix(BigDenseMatrix matrix)` create DMatrix from a BigDenseMatrix
    `DMatrix(BigDenseMatrix matrix, float missing)` create DMatrix from dense matrix
    `DMatrix(ColumnBatch columnBatch, float missing, int nthread)` Create the normal DMatrix from column array interface
    `DMatrix(float[] data, int nrow, int ncol)` Deprecated. Please specify the missing value explicitly using `DMatrix(float[], int, int, float)`
    `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
    `ExternalCheckpointManager(String checkpointPath, org.apache.hadoop.fs.FileSystem fs)`
    `RabitTracker(int numWorkers)`
    `RabitTracker(int numWorkers, String hostIp, String pythonExec)`

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