Merge pull request #733 from damiencarol/javadocfix

[Java] Fix broken javadoc generation

java/xgboost4j/src/main/java/org/dmlc/xgboost4j/Booster.java

@@ -59,7 +59,7 @@ public final class Booster {
      * init Booster from dMatrixs
      * @param params parameters
      * @param dMatrixs DMatrix array
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public Booster(Iterable<Entry<String, Object>> params, DMatrix[] dMatrixs) throws XGBoostError {
         init(dMatrixs);
@@ -73,7 +73,7 @@ public final class Booster {
      * load model from modelPath
      * @param params parameters
      * @param modelPath booster modelPath (model generated by booster.saveModel)
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public Booster(Iterable<Entry<String, Object>> params, String modelPath) throws XGBoostError {
         init(null);
@@ -103,7 +103,7 @@ public final class Booster {
      * set parameter
      * @param key param name
      * @param value param value
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public final void setParam(String key, String value) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGBoosterSetParam(handle, key, value));
@@ -112,7 +112,7 @@ public final class Booster {
     /**
      * set parameters
      * @param params parameters key-value map 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void setParams(Iterable<Entry<String, Object>> params) throws XGBoostError {
         if(params!=null) {
@@ -127,7 +127,7 @@ public final class Booster {
      * Update (one iteration)
      * @param dtrain training data
      * @param iter current iteration number
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void update(DMatrix dtrain, int iter) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGBoosterUpdateOneIter(handle, iter, dtrain.getHandle()));
@@ -138,7 +138,7 @@ public final class Booster {
      * @param dtrain training data
      * @param iter current iteration number
      * @param obj customized objective class
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void update(DMatrix dtrain, int iter, IObjective obj) throws XGBoostError {
         float[][] predicts = predict(dtrain, true);
@@ -151,7 +151,7 @@ public final class Booster {
      * @param dtrain training data
      * @param grad first order of gradient
      * @param hess seconde order of gradient
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void boost(DMatrix dtrain, float[] grad, float[] hess) throws XGBoostError {
         if(grad.length != hess.length) {
@@ -166,7 +166,7 @@ public final class Booster {
      * @param evalNames name for eval dmatrixs, used for check results
      * @param iter current eval iteration
      * @return eval information
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public String evalSet(DMatrix[] evalMatrixs, String[] evalNames,  int iter) throws XGBoostError {
         long[] handles = dMatrixs2handles(evalMatrixs);
@@ -177,12 +177,12 @@ public final class Booster {
     
     /**
      * evaluate with given customized Evaluation class
-     * @param evalMatrixs
-     * @param evalNames
-     * @param iter
-     * @param eval
+     * @param evalMatrixs evaluation matrix
+     * @param evalNames evaluation names
+     * @param iter number of interations
+     * @param eval custom evaluator
      * @return eval information
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public String evalSet(DMatrix[] evalMatrixs, String[] evalNames,  int iter, IEvaluation eval) throws XGBoostError {
         String evalInfo = "";
@@ -202,7 +202,7 @@ public final class Booster {
      * @param evalNames name for eval dmatrixs, used for check results
      * @param iter current eval iteration
      * @return eval information
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public String evalSet(long[] dHandles, String[] evalNames,  int iter) throws XGBoostError {
         String[] evalInfo = new String[1];
@@ -213,11 +213,11 @@ public final class Booster {
     
     /**
      * evaluate with given dmatrix, similar to evalSet
-     * @param evalMat
-     * @param evalName
-     * @param iter
+     * @param evalMat evaluation matrix
+     * @param evalName evaluation name
+     * @param iter number of iterations
      * @return eval information
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public String eval(DMatrix evalMat, String evalName, int iter) throws XGBoostError {
         DMatrix[] evalMats = new DMatrix[] {evalMat};
@@ -227,10 +227,10 @@ public final class Booster {
     
     /**
      * base function for Predict
-     * @param data
-     * @param outPutMargin
-     * @param treeLimit
-     * @param predLeaf
+     * @param data data
+     * @param outPutMargin output margin
+     * @param treeLimit limit number of trees
+     * @param predLeaf prediction minimum to keep leafs
      * @return predict results
      */
     private synchronized float[][] pred(DMatrix data, boolean outPutMargin, int treeLimit, boolean predLeaf) throws XGBoostError {
@@ -259,7 +259,7 @@ public final class Booster {
      * Predict with data
      * @param data dmatrix storing the input
      * @return predict result 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public float[][] predict(DMatrix data) throws XGBoostError {
         return pred(data, false, 0, false);
@@ -270,7 +270,7 @@ public final class Booster {
      * @param data dmatrix storing the input
      * @param outPutMargin Whether to output the raw untransformed margin value.
      * @return predict result
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public float[][] predict(DMatrix data, boolean outPutMargin) throws XGBoostError {
         return pred(data, outPutMargin, 0, false);
@@ -282,7 +282,7 @@ public final class Booster {
      * @param outPutMargin Whether to output the raw untransformed margin value.
      * @param treeLimit Limit number of trees in the prediction; defaults to 0 (use all trees).
      * @return predict result
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public float[][] predict(DMatrix data, boolean outPutMargin, int treeLimit) throws XGBoostError {
         return pred(data, outPutMargin, treeLimit, false);
@@ -297,7 +297,7 @@ public final class Booster {
             Note that the leaf index of a tree is unique per tree, so you may find leaf 1
             in both tree 1 and tree 0.
      * @return predict result
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public float[][] predict(DMatrix data , int treeLimit, boolean predLeaf) throws XGBoostError {
         return pred(data, false, treeLimit, predLeaf);
@@ -305,7 +305,7 @@ public final class Booster {
     
     /**
      * save model to modelPath
-     * @param modelPath 
+     * @param modelPath model path
      */
     public void saveModel(String modelPath) {
         XgboostJNI.XGBoosterSaveModel(handle, modelPath);
@@ -319,7 +319,7 @@ public final class Booster {
      * get the dump of the model as a string array
      * @param withStats Controls whether the split statistics are output.
      * @return dumped model information
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public String[] getDumpInfo(boolean withStats) throws XGBoostError {
         int statsFlag = 0;
@@ -336,7 +336,7 @@ public final class Booster {
      * @param featureMap featureMap file
      * @param withStats Controls whether the split statistics are output.
      * @return dumped model information
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public String[] getDumpInfo(String featureMap, boolean withStats) throws XGBoostError {
         int statsFlag = 0;
@@ -353,10 +353,10 @@ public final class Booster {
      * @param modelPath file to save dumped model info
      * @param withStats bool
             Controls whether the split statistics are output.
-     * @throws FileNotFoundException
-     * @throws UnsupportedEncodingException
-     * @throws IOException 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @throws FileNotFoundException file not found
+     * @throws UnsupportedEncodingException unsupported feature
+     * @throws IOException error with model writing
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void dumpModel(String modelPath, boolean withStats) throws FileNotFoundException, UnsupportedEncodingException, IOException, XGBoostError {
         File tf = new File(modelPath);
@@ -380,10 +380,10 @@ public final class Booster {
      * @param featureMap featureMap file
      * @param withStats bool
             Controls whether the split statistics are output.
-     * @throws FileNotFoundException
-     * @throws UnsupportedEncodingException
-     * @throws IOException 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @throws FileNotFoundException exception
+     * @throws UnsupportedEncodingException exception
+     * @throws IOException exception
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void dumpModel(String modelPath, String featureMap, boolean withStats) throws FileNotFoundException, UnsupportedEncodingException, IOException, XGBoostError {
         File tf = new File(modelPath);
@@ -404,7 +404,7 @@ public final class Booster {
     /**
      * get importance of each feature
      * @return featureMap  key: feature index, value: feature importance score
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public Map<String, Integer> getFeatureScore() throws XGBoostError {
         String[] modelInfos = getDumpInfo(false);
@@ -433,7 +433,7 @@ public final class Booster {
      * get importance of each feature
      * @param featureMap file to save dumped model info
      * @return featureMap  key: feature index, value: feature importance score
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public Map<String, Integer> getFeatureScore(String featureMap) throws XGBoostError {
         String[] modelInfos = getDumpInfo(featureMap, false);

java/xgboost4j/src/main/java/org/dmlc/xgboost4j/DMatrix.java

@@ -51,8 +51,8 @@ public class DMatrix {
     
     /**
      *  init DMatrix from file (svmlight format)
-     * @param dataPath 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @param dataPath path of data file
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public DMatrix(String dataPath) throws XGBoostError {
         if(dataPath == null) {
@@ -69,7 +69,7 @@ public class DMatrix {
      * @param indices Indices (colIndexs for CSR or rowIndexs for CSC)
      * @param data non zero values (sequence by row for CSR or by col for CSC)
      * @param st sparse matrix type (CSR or CSC)
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public DMatrix(long[] headers, int[] indices, float[] data, SparseType st) throws XGBoostError {
         long[] out = new long[1];
@@ -90,7 +90,7 @@ public class DMatrix {
      * @param data data values
      * @param nrow number of rows
      * @param ncol number of columns
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public DMatrix(float[] data, int nrow, int ncol) throws XGBoostError {
         long[] out = new long[1];
@@ -110,7 +110,8 @@ public class DMatrix {
     
     /**
      * set label of dmatrix
-     * @param labels 
+     * @param labels labels
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void setLabel(float[] labels) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "label", labels));
@@ -118,8 +119,8 @@ public class DMatrix {
     
     /**
      * set weight of each instance
-     * @param weights 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @param weights weights
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void setWeight(float[] weights) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "weight", weights));
@@ -128,8 +129,8 @@ public class DMatrix {
     /**
      * if specified, xgboost will start from this init margin
      * can be used to specify initial prediction to boost from
-     * @param baseMargin 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @param baseMargin base margin
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void setBaseMargin(float[] baseMargin) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "base_margin", baseMargin));
@@ -138,8 +139,8 @@ public class DMatrix {
     /**
      * if specified, xgboost will start from this init margin
      * can be used to specify initial prediction to boost from
-     * @param baseMargin 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @param baseMargin base margin
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void setBaseMargin(float[][] baseMargin) throws XGBoostError {
         float[] flattenMargin = flatten(baseMargin);
@@ -148,8 +149,8 @@ public class DMatrix {
     
     /**
      * Set group sizes of DMatrix (used for ranking)
-     * @param group 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @param group group size as array
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void setGroup(int[] group) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetGroup(handle, group));
@@ -170,7 +171,7 @@ public class DMatrix {
     /**
      * get label values
      * @return label
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public float[] getLabel() throws XGBoostError {
         return getFloatInfo("label");
@@ -179,7 +180,7 @@ public class DMatrix {
     /**
      * get weight of the DMatrix
      * @return weights
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public float[] getWeight() throws XGBoostError {
         return getFloatInfo("weight");
@@ -188,7 +189,7 @@ public class DMatrix {
     /**
      * get base margin of the DMatrix
      * @return base margin
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public float[] getBaseMargin() throws XGBoostError {
         return getFloatInfo("base_margin");
@@ -196,9 +197,9 @@ public class DMatrix {
     
     /**
      * Slice the DMatrix and return a new DMatrix that only contains `rowIndex`.
-     * @param rowIndex
+     * @param rowIndex row index
      * @return sliced new DMatrix
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public DMatrix slice(int[] rowIndex) throws XGBoostError {
         long[] out = new long[1];
@@ -211,7 +212,7 @@ public class DMatrix {
     /**
      * get the row number of DMatrix
      * @return number of rows
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public long rowNum() throws XGBoostError {
         long[] rowNum = new long[1];
@@ -221,12 +222,16 @@ public class DMatrix {
     
     /**
      * save DMatrix to filePath
-     * @param filePath 
+     * @param filePath file path
      */
     public void saveBinary(String filePath) {
         XgboostJNI.XGDMatrixSaveBinary(handle, filePath, 1);
     }
     
+    /**
+     * Get the handle
+     * @return native handler id
+     */
     public long getHandle() {
         return handle;
     }

java/xgboost4j/src/main/java/org/dmlc/xgboost4j/IEvaluation.java

@@ -16,21 +16,26 @@
 package org.dmlc.xgboost4j;
 
 /**
- *  interface for customized evaluation
+ * interface for customized evaluation
+ * 
  * @author hzx
  */
-public interface IEvaluation {    
-    /**
-     * get evaluate metric
-     * @return evalMetric
-     */
-    public abstract String getMetric();
-    
-    /**
-     * evaluate with predicts and data
-     * @param predicts
-     * @param dmat
-     * @return 
-     */
-    public abstract float eval(float[][] predicts, DMatrix dmat);
+public interface IEvaluation {
+	/**
+	 * get evaluate metric
+	 * 
+	 * @return evalMetric
+	 */
+	public abstract String getMetric();
+
+	/**
+	 * evaluate with predicts and data
+	 * 
+	 * @param predicts
+	 *            predictions as array
+	 * @param dmat
+	 *            data matrix to evaluate
+	 * @return result of the metric
+	 */
+	public abstract float eval(float[][] predicts, DMatrix dmat);
 }

java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/CVPack.java

@@ -37,7 +37,7 @@ public class CVPack {
      * @param dtrain train data
      * @param dtest test data
      * @param params parameters
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public CVPack(DMatrix dtrain, DMatrix dtest, Iterable<Map.Entry<String, Object>> params) throws XGBoostError {
         dmats = new DMatrix[] {dtrain, dtest};
@@ -50,7 +50,7 @@ public class CVPack {
     /**
      * update one iteration
      * @param iter iteration num
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void update(int iter) throws XGBoostError {
         booster.update(dtrain, iter);
@@ -60,7 +60,7 @@ public class CVPack {
      * update one iteration
      * @param iter iteration num
      * @param obj customized objective
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public void update(int iter, IObjective obj) throws XGBoostError {
         booster.update(dtrain, iter, obj);
@@ -69,8 +69,8 @@ public class CVPack {
     /**
      * evaluation 
      * @param iter iteration num
-     * @return 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @return evaluation
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public String eval(int iter) throws XGBoostError {
         return booster.evalSet(dmats, names, iter);
@@ -80,8 +80,8 @@ public class CVPack {
      * evaluation 
      * @param iter iteration num
      * @param eval customized eval
-     * @return 
-     * @throws org.dmlc.xgboost4j.util.XGBoostError 
+     * @return evaluation
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public String eval(int iter, IEvaluation eval) throws XGBoostError {
         return booster.evalSet(dmats, names, iter, eval);

java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/ErrorHandle.java

@@ -21,8 +21,7 @@ import org.apache.commons.logging.LogFactory;
 import org.dmlc.xgboost4j.wrapper.XgboostJNI;
 
 /**
- * error handle for Xgboost
- * @author hzx
+ * Error handle for Xgboost.
  */
 public class ErrorHandle {
     private static final Log logger = LogFactory.getLog(ErrorHandle.class);
@@ -38,9 +37,9 @@ public class ErrorHandle {
     }
     
     /**
-     * check the return value of C API
+     * Check the return value of C API.
      * @param ret return valud of xgboostJNI C API call
-     * @throws org.dmlc.xgboost4j.util.XGBoostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public static void checkCall(int ret) throws XGBoostError {
         if(ret != 0) {

java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/Initializer.java

@@ -44,8 +44,8 @@ public class Initializer {
     
     /**
      * load native library, this method will first try to load library from java.library.path, then try to load library in jar package.
-     * @param libName
-     * @throws IOException 
+     * @param libName library path
+     * @throws IOException exception 
      */
     private static void smartLoad(String libName) throws IOException {
         addNativeDir(nativePath);
@@ -63,9 +63,9 @@ public class Initializer {
     }
     
     /**
-     * add libPath to java.library.path, then native library in libPath would be load properly
-     * @param libPath
-     * @throws IOException 
+     * Add libPath to java.library.path, then native library in libPath would be load properly
+     * @param libPath library path
+     * @throws IOException exception
      */
     public static void addNativeDir(String libPath) throws IOException {
         try {

java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/NativeUtils.java

@@ -25,10 +25,11 @@ import java.io.OutputStream;
 
 /**
  * Simple library class for working with JNI (Java Native Interface)
- * 
- * @see http://adamheinrich.com/2012/how-to-load-native-jni-library-from-jar
- *
- * @author Adam Heirnich <adam@adamh.cz>, http://www.adamh.cz
+ * <p>
+ * See <a href="http://adamheinrich.com/2012/how-to-load-native-jni-library-from-jar">
+ *   http://adamheinrich.com/2012/how-to-load-native-jni-library-from-jar</a>
+ * <p>
+ * Author Adam Heirnich &lt;adam@adamh.cz&gt;, http://www.adamh.cz
  */
 public class NativeUtils {
  
@@ -40,14 +41,17 @@ public class NativeUtils {
  
     /**
      * Loads library from current JAR archive
-     * 
-     * The file from JAR is copied into system temporary directory and then loaded. The temporary file is deleted after exiting.
+     * <p>
+     * The file from JAR is copied into system temporary directory and then loaded. 
+     * The temporary file is deleted after exiting.
      * Method uses String as filename because the pathname is "abstract", not system-dependent.
+     * <p>
+     * The restrictions of {@link File#createTempFile(java.lang.String, java.lang.String)} apply to {@code path}.
      * 
      * @param path The filename inside JAR as absolute path (beginning with '/'), e.g. /package/File.ext
      * @throws IOException If temporary file creation or read/write operation fails
      * @throws IllegalArgumentException If source file (param path) does not exist
-     * @throws IllegalArgumentException If the path is not absolute or if the filename is shorter than three characters (restriction of {@see File#createTempFile(java.lang.String, java.lang.String)}).
+     * @throws IllegalArgumentException If the path is not absolute or if the filename is shorter than three characters 
      */
     public static void loadLibraryFromJar(String path) throws IOException {
  

java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/Trainer.java

@@ -45,6 +45,7 @@ public class Trainer {
      * @param obj customized objective (set to null if not used)
      * @param eval customized evaluation (set to null if not used)
      * @return trained booster
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public static Booster train(Iterable<Entry<String, Object>> params, DMatrix dtrain, int round, 
             Iterable<Entry<String, DMatrix>> watchs, IObjective obj, IEvaluation eval) throws XGBoostError {
@@ -111,6 +112,7 @@ public class Trainer {
      * @param obj customized objective (set to null if not used)
      * @param eval customized evaluation (set to null if not used)
      * @return evaluation history
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public static String[] crossValiation(Iterable<Entry<String, Object>> params, DMatrix data, int round, int nfold, String[] metrics, IObjective obj, IEvaluation eval) throws XGBoostError {
         CVPack[] cvPacks = makeNFold(data, nfold, params, metrics);
@@ -148,6 +150,7 @@ public class Trainer {
      * @param params booster parameters
      * @param evalMetrics Evaluation metrics
      * @return CV package array
+     * @throws org.dmlc.xgboost4j.util.XGBoostError native error
      */
     public static CVPack[] makeNFold(DMatrix data, int nfold, Iterable<Entry<String, Object>> params, String[] evalMetrics) throws XGBoostError {
         List<Integer> samples = genRandPermutationNums(0, (int) data.rowNum());