## Uses of Class
ml.dmlc.xgboost4j.java.DMatrix

- Packages that use DMatrix
  Package | Description
  --- | ---
  ml.dmlc.xgboost4j.java |

- - ### Uses of DMatrix in ml.dmlc.xgboost4j.java

    Methods in ml.dmlc.xgboost4j.java that return DMatrix
    Modifier and Type | Method and Description
    --- | ---
    `DMatrix` | DMatrix.`slice(int[] rowIndex)` Slice the DMatrix and return a new DMatrix that only contains `rowIndex`.

    Methods in ml.dmlc.xgboost4j.java with parameters of type DMatrix
    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

    Method parameters in ml.dmlc.xgboost4j.java with type arguments of type DMatrix
    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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