diff --git a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/BasicWalkThrough.java b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/BasicWalkThrough.java
index 86ba49c48..0c6529d2c 100644
--- a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/BasicWalkThrough.java
+++ b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/BasicWalkThrough.java
@@ -31,7 +31,7 @@ import org.dmlc.xgboost4j.DMatrix;
 import org.dmlc.xgboost4j.demo.util.DataLoader;
 import org.dmlc.xgboost4j.demo.util.Params;
 import org.dmlc.xgboost4j.util.Trainer;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 
 /**
  * a simple example of java wrapper for xgboost
@@ -53,7 +53,7 @@ public class BasicWalkThrough {
     }
     
     
-    public static void main(String[] args) throws UnsupportedEncodingException, IOException, XgboostError {
+    public static void main(String[] args) throws UnsupportedEncodingException, IOException, XGBoostError {
         // load file from text file, also binary buffer generated by xgboost4j
         DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
         DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
diff --git a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/BoostFromPrediction.java b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/BoostFromPrediction.java
index 1113eef68..a81da0c59 100644
--- a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/BoostFromPrediction.java
+++ b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/BoostFromPrediction.java
@@ -23,14 +23,14 @@ import org.dmlc.xgboost4j.Booster;
 import org.dmlc.xgboost4j.DMatrix;
 import org.dmlc.xgboost4j.demo.util.Params;
 import org.dmlc.xgboost4j.util.Trainer;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 
 /**
  * example for start from a initial base prediction
  * @author hzx
  */
 public class BoostFromPrediction {
-    public static void main(String[] args) throws XgboostError {
+    public static void main(String[] args) throws XGBoostError {
         System.out.println("start running example to start from a initial prediction");
         
         // load file from text file, also binary buffer generated by xgboost4j
diff --git a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/CrossValidation.java b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/CrossValidation.java
index ec5716700..6dcf917da 100644
--- a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/CrossValidation.java
+++ b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/CrossValidation.java
@@ -19,14 +19,14 @@ import java.io.IOException;
 import org.dmlc.xgboost4j.DMatrix;
 import org.dmlc.xgboost4j.util.Trainer;
 import org.dmlc.xgboost4j.demo.util.Params;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 
 /**
  * an example of cross validation
  * @author hzx
  */
 public class CrossValidation {
-    public static void main(String[] args) throws IOException, XgboostError {
+    public static void main(String[] args) throws IOException, XGBoostError {
          //load train mat
         DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
         
diff --git a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/CustomObjective.java b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/CustomObjective.java
index 4aaa053e0..2b8c44ecd 100644
--- a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/CustomObjective.java
+++ b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/CustomObjective.java
@@ -27,7 +27,7 @@ import org.dmlc.xgboost4j.DMatrix;
 import org.dmlc.xgboost4j.IObjective;
 import org.dmlc.xgboost4j.demo.util.Params;
 import org.dmlc.xgboost4j.util.Trainer;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 
 /**
  * an example user define objective and eval
@@ -74,7 +74,7 @@ public class CustomObjective {
             float[] labels;
             try {
                 labels = dtrain.getLabel();
-            } catch (XgboostError ex) {
+            } catch (XGBoostError ex) {
                 logger.error(ex);
                 return null;
             }
@@ -122,7 +122,7 @@ public class CustomObjective {
             float[] labels;
             try {
                 labels = dmat.getLabel();
-            } catch (XgboostError ex) {
+            } catch (XGBoostError ex) {
                 logger.error(ex);
                 return -1f;
             }
@@ -140,7 +140,7 @@ public class CustomObjective {
         }
     }
     
-    public static void main(String[] args) throws XgboostError {
+    public static void main(String[] args) throws XGBoostError {
         //load train mat (svmlight format)
         DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
         //load valid mat (svmlight format)
diff --git a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/ExternalMemory.java b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/ExternalMemory.java
index e74e3e858..b0a9d27dc 100644
--- a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/ExternalMemory.java
+++ b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/ExternalMemory.java
@@ -23,14 +23,14 @@ import org.dmlc.xgboost4j.Booster;
 import org.dmlc.xgboost4j.DMatrix;
 import org.dmlc.xgboost4j.demo.util.Params;
 import org.dmlc.xgboost4j.util.Trainer;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 
 /**
  * simple example for using external memory version
  * @author hzx
  */
 public class ExternalMemory {
-    public static void main(String[] args) throws XgboostError {
+    public static void main(String[] args) throws XGBoostError {
         //this is the only difference, add a # followed by a cache prefix name
         //several cache file with the prefix will be generated
         //currently only support convert from libsvm file
diff --git a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/GeneralizedLinearModel.java b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/GeneralizedLinearModel.java
index db3cd0e59..7d3d717bd 100644
--- a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/GeneralizedLinearModel.java
+++ b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/GeneralizedLinearModel.java
@@ -24,7 +24,7 @@ import org.dmlc.xgboost4j.DMatrix;
 import org.dmlc.xgboost4j.demo.util.CustomEval;
 import org.dmlc.xgboost4j.demo.util.Params;
 import org.dmlc.xgboost4j.util.Trainer;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 
 /**
  * this is an example of fit generalized linear model in xgboost
@@ -32,7 +32,7 @@ import org.dmlc.xgboost4j.util.XgboostError;
  * @author hzx
  */
 public class GeneralizedLinearModel {
-    public static void main(String[] args) throws XgboostError {
+    public static void main(String[] args) throws XGBoostError {
         // load file from text file, also binary buffer generated by xgboost4j
         DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
         DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
diff --git a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/PredictFirstNtree.java b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/PredictFirstNtree.java
index 6bcf67f86..2bbd1fd6c 100644
--- a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/PredictFirstNtree.java
+++ b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/PredictFirstNtree.java
@@ -25,14 +25,14 @@ import org.dmlc.xgboost4j.util.Trainer;
 
 import org.dmlc.xgboost4j.demo.util.CustomEval;
 import org.dmlc.xgboost4j.demo.util.Params;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 
 /**
  * predict first ntree
  * @author hzx
  */
 public class PredictFirstNtree {   
-    public static void main(String[] args) throws XgboostError {
+    public static void main(String[] args) throws XGBoostError {
         // load file from text file, also binary buffer generated by xgboost4j
         DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
         DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
diff --git a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/PredictLeafIndices.java b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/PredictLeafIndices.java
index 61026a6b8..ede103aeb 100644
--- a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/PredictLeafIndices.java
+++ b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/PredictLeafIndices.java
@@ -24,14 +24,14 @@ import org.dmlc.xgboost4j.Booster;
 import org.dmlc.xgboost4j.DMatrix;
 import org.dmlc.xgboost4j.util.Trainer;
 import org.dmlc.xgboost4j.demo.util.Params;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 
 /**
  * predict leaf indices
  * @author hzx
  */
 public class PredictLeafIndices {
-    public static void main(String[] args) throws XgboostError {
+    public static void main(String[] args) throws XGBoostError {
         // load file from text file, also binary buffer generated by xgboost4j
         DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
         DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
diff --git a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/util/CustomEval.java b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/util/CustomEval.java
index 116c06ddf..5f25278d5 100644
--- a/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/util/CustomEval.java
+++ b/java/xgboost4j-demo/src/main/java/org/dmlc/xgboost4j/demo/util/CustomEval.java
@@ -19,7 +19,7 @@ import org.apache.commons.logging.Log;
 import org.apache.commons.logging.LogFactory;
 import org.dmlc.xgboost4j.DMatrix;
 import org.dmlc.xgboost4j.IEvaluation;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 
 /**
  * a util evaluation class for examples
@@ -41,7 +41,7 @@ public class CustomEval implements IEvaluation {
         float[] labels;
         try {
             labels = dmat.getLabel();
-        } catch (XgboostError ex) {
+        } catch (XGBoostError ex) {
             logger.error(ex);
             return -1f;
         }
diff --git a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/Booster.java b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/Booster.java
index 0f296241b..51fee441e 100644
--- a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/Booster.java
+++ b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/Booster.java
@@ -31,7 +31,7 @@ import org.apache.commons.logging.LogFactory;
 
 import org.dmlc.xgboost4j.util.Initializer;
 import org.dmlc.xgboost4j.util.ErrorHandle;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 import org.dmlc.xgboost4j.wrapper.XgboostJNI;
 
 
@@ -59,9 +59,9 @@ 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
      */
-    public Booster(Iterable<Entry<String, Object>> params, DMatrix[] dMatrixs) throws XgboostError {
+    public Booster(Iterable<Entry<String, Object>> params, DMatrix[] dMatrixs) throws XGBoostError {
         init(dMatrixs);
         setParam("seed","0");
         setParams(params);
@@ -73,9 +73,9 @@ 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
      */
-    public Booster(Iterable<Entry<String, Object>> params, String modelPath) throws XgboostError {
+    public Booster(Iterable<Entry<String, Object>> params, String modelPath) throws XGBoostError {
         long[] out = new long[1];
         init(null);
         loadModel(modelPath);
@@ -86,7 +86,7 @@ public final class Booster {
   
     
     
-    private void init(DMatrix[] dMatrixs) throws XgboostError {
+    private void init(DMatrix[] dMatrixs) throws XGBoostError {
         long[] handles = null;
         if(dMatrixs != null) {
             handles = dMatrixs2handles(dMatrixs);
@@ -101,18 +101,18 @@ 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
      */
-    public final void setParam(String key, String value) throws XgboostError {
+    public final void setParam(String key, String value) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGBoosterSetParam(handle, key, value));
     }
     
     /**
      * set parameters
      * @param params parameters key-value map 
-     * @throws org.dmlc.xgboost4j.util.XgboostError 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
-    public void setParams(Iterable<Entry<String, Object>> params) throws XgboostError {
+    public void setParams(Iterable<Entry<String, Object>> params) throws XGBoostError {
         if(params!=null) {
             for(Map.Entry<String, Object> entry : params) {
                 setParam(entry.getKey(), entry.getValue().toString());
@@ -125,9 +125,9 @@ 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
      */
-    public void update(DMatrix dtrain, int iter) throws XgboostError {
+    public void update(DMatrix dtrain, int iter) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGBoosterUpdateOneIter(handle, iter, dtrain.getHandle()));
     }
     
@@ -136,9 +136,9 @@ 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
      */
-    public void update(DMatrix dtrain, int iter, IObjective obj) throws XgboostError {
+    public void update(DMatrix dtrain, int iter, IObjective obj) throws XGBoostError {
         float[][] predicts = predict(dtrain, true);
         List<float[]> gradients = obj.getGradient(predicts, dtrain);
         boost(dtrain, gradients.get(0), gradients.get(1));
@@ -149,9 +149,9 @@ 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
      */
-    public void boost(DMatrix dtrain, float[] grad, float[] hess) throws XgboostError {
+    public void boost(DMatrix dtrain, float[] grad, float[] hess) throws XGBoostError {
         if(grad.length != hess.length) {
             throw new AssertionError(String.format("grad/hess length mismatch %s / %s", grad.length, hess.length));
         }
@@ -164,9 +164,9 @@ 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
      */
-    public String evalSet(DMatrix[] evalMatrixs, String[] evalNames,  int iter) throws XgboostError {
+    public String evalSet(DMatrix[] evalMatrixs, String[] evalNames,  int iter) throws XGBoostError {
         long[] handles = dMatrixs2handles(evalMatrixs);
         String[] evalInfo = new String[1];
         ErrorHandle.checkCall(XgboostJNI.XGBoosterEvalOneIter(handle, iter, handles, evalNames, evalInfo));
@@ -180,9 +180,9 @@ public final class Booster {
      * @param iter
      * @param eval
      * @return eval information
-     * @throws org.dmlc.xgboost4j.util.XgboostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError
      */
-    public String evalSet(DMatrix[] evalMatrixs, String[] evalNames,  int iter, IEvaluation eval) throws XgboostError {
+    public String evalSet(DMatrix[] evalMatrixs, String[] evalNames,  int iter, IEvaluation eval) throws XGBoostError {
         String evalInfo = "";
         for(int i=0; i<evalNames.length; i++) {
             String evalName = evalNames[i];
@@ -200,9 +200,9 @@ 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
      */
-    public String evalSet(long[] dHandles, String[] evalNames,  int iter) throws XgboostError {
+    public String evalSet(long[] dHandles, String[] evalNames,  int iter) throws XGBoostError {
         String[] evalInfo = new String[1];
         ErrorHandle.checkCall(XgboostJNI.XGBoosterEvalOneIter(handle, iter, dHandles, evalNames, evalInfo));
         return evalInfo[0];
@@ -215,9 +215,9 @@ public final class Booster {
      * @param evalName
      * @param iter
      * @return eval information
-     * @throws org.dmlc.xgboost4j.util.XgboostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError
      */
-    public String eval(DMatrix evalMat, String evalName, int iter) throws XgboostError {
+    public String eval(DMatrix evalMat, String evalName, int iter) throws XGBoostError {
         DMatrix[] evalMats = new DMatrix[] {evalMat};
         String[] evalNames = new String[] {evalName};
         return  evalSet(evalMats, evalNames, iter);
@@ -231,7 +231,7 @@ public final class Booster {
      * @param predLeaf
      * @return predict results
      */
-    private synchronized float[][] pred(DMatrix data, boolean outPutMargin, long treeLimit, boolean predLeaf) throws XgboostError {
+    private synchronized float[][] pred(DMatrix data, boolean outPutMargin, long treeLimit, boolean predLeaf) throws XGBoostError {
         int optionMask = 0;
         if(outPutMargin) {
             optionMask = 1;
@@ -257,9 +257,9 @@ 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 
      */
-    public float[][] predict(DMatrix data) throws XgboostError {
+    public float[][] predict(DMatrix data) throws XGBoostError {
         return pred(data, false, 0, false);
     }
     
@@ -268,9 +268,9 @@ 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
      */
-    public float[][] predict(DMatrix data, boolean outPutMargin) throws XgboostError {
+    public float[][] predict(DMatrix data, boolean outPutMargin) throws XGBoostError {
         return pred(data, outPutMargin, 0, false);
     }
     
@@ -280,9 +280,9 @@ 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
      */
-    public float[][] predict(DMatrix data, boolean outPutMargin, long treeLimit) throws XgboostError {
+    public float[][] predict(DMatrix data, boolean outPutMargin, long treeLimit) throws XGBoostError {
         return pred(data, outPutMargin, treeLimit, false);
     }
     
@@ -295,9 +295,9 @@ 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
      */
-    public float[][] predict(DMatrix data , long treeLimit, boolean predLeaf) throws XgboostError {
+    public float[][] predict(DMatrix data , long treeLimit, boolean predLeaf) throws XGBoostError {
         return pred(data, false, treeLimit, predLeaf);
     }
     
@@ -317,9 +317,9 @@ 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
      */
-    public String[] getDumpInfo(boolean withStats) throws XgboostError {
+    public String[] getDumpInfo(boolean withStats) throws XGBoostError {
         int statsFlag = 0;
         if(withStats) {
             statsFlag = 1;
@@ -334,9 +334,9 @@ 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
      */
-    public String[] getDumpInfo(String featureMap, boolean withStats) throws XgboostError {
+    public String[] getDumpInfo(String featureMap, boolean withStats) throws XGBoostError {
         int statsFlag = 0;
         if(withStats) {
             statsFlag = 1;
@@ -354,9 +354,9 @@ public final class Booster {
      * @throws FileNotFoundException
      * @throws UnsupportedEncodingException
      * @throws IOException 
-     * @throws org.dmlc.xgboost4j.util.XgboostError 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
-    public void dumpModel(String modelPath, boolean withStats) throws FileNotFoundException, UnsupportedEncodingException, IOException, XgboostError {
+    public void dumpModel(String modelPath, boolean withStats) throws FileNotFoundException, UnsupportedEncodingException, IOException, XGBoostError {
         File tf = new File(modelPath);
         FileOutputStream out = new FileOutputStream(tf);
         BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(out, "UTF-8"));
@@ -381,9 +381,9 @@ public final class Booster {
      * @throws FileNotFoundException
      * @throws UnsupportedEncodingException
      * @throws IOException 
-     * @throws org.dmlc.xgboost4j.util.XgboostError 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
-    public void dumpModel(String modelPath, String featureMap, boolean withStats) throws FileNotFoundException, UnsupportedEncodingException, IOException, XgboostError {
+    public void dumpModel(String modelPath, String featureMap, boolean withStats) throws FileNotFoundException, UnsupportedEncodingException, IOException, XGBoostError {
         File tf = new File(modelPath);
         FileOutputStream out = new FileOutputStream(tf);
         BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(out, "UTF-8"));
@@ -402,9 +402,9 @@ 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
      */
-    public Map<String, Integer> getFeatureScore() throws XgboostError {
+    public Map<String, Integer> getFeatureScore() throws XGBoostError {
         String[] modelInfos = getDumpInfo(false);
         Map<String, Integer> featureScore = new HashMap<>();
         for(String tree : modelInfos) {
@@ -431,9 +431,9 @@ 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
      */
-    public Map<String, Integer> getFeatureScore(String featureMap) throws XgboostError {
+    public Map<String, Integer> getFeatureScore(String featureMap) throws XGBoostError {
         String[] modelInfos = getDumpInfo(featureMap, false);
         Map<String, Integer> featureScore = new HashMap<>();
         for(String tree : modelInfos) {
diff --git a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/DMatrix.java b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/DMatrix.java
index b056cad09..61db98a6d 100644
--- a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/DMatrix.java
+++ b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/DMatrix.java
@@ -19,7 +19,7 @@ import java.io.IOException;
 import org.apache.commons.logging.Log;
 import org.apache.commons.logging.LogFactory;
 import org.dmlc.xgboost4j.util.ErrorHandle;
-import org.dmlc.xgboost4j.util.XgboostError;
+import org.dmlc.xgboost4j.util.XGBoostError;
 import org.dmlc.xgboost4j.util.Initializer;
 import org.dmlc.xgboost4j.wrapper.XgboostJNI;
 
@@ -52,9 +52,9 @@ public class DMatrix {
     /**
      *  init DMatrix from file (svmlight format)
      * @param dataPath 
-     * @throws org.dmlc.xgboost4j.util.XgboostError 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
-    public DMatrix(String dataPath) throws XgboostError {
+    public DMatrix(String dataPath) throws XGBoostError {
         long[] out = new long[1];
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromFile(dataPath, 1, out));
         handle = out[0];
@@ -66,9 +66,9 @@ 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
      */
-    public DMatrix(long[] headers, int[] indices, float[] data, SparseType st) throws XgboostError {
+    public DMatrix(long[] headers, int[] indices, float[] data, SparseType st) throws XGBoostError {
         long[] out = new long[1];
         if(st == SparseType.CSR) {
             ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromCSR(headers, indices, data, out));
@@ -87,9 +87,9 @@ 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
      */
-    public DMatrix(float[] data, int nrow, int ncol) throws XgboostError {
+    public DMatrix(float[] data, int nrow, int ncol) throws XGBoostError {
         long[] out = new long[1];
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromMat(data, nrow, ncol, 0.0f, out));
         handle = out[0];
@@ -109,16 +109,16 @@ public class DMatrix {
      * set label of dmatrix
      * @param labels 
      */
-    public void setLabel(float[] labels) throws XgboostError {
+    public void setLabel(float[] labels) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "label", labels));
     }
     
     /**
      * set weight of each instance
      * @param weights 
-     * @throws org.dmlc.xgboost4j.util.XgboostError 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
-    public void setWeight(float[] weights) throws XgboostError {
+    public void setWeight(float[] weights) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "weight", weights));
     }
     
@@ -126,9 +126,9 @@ 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 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
-    public void setBaseMargin(float[] baseMargin) throws XgboostError {
+    public void setBaseMargin(float[] baseMargin) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "base_margin", baseMargin));
     }
     
@@ -136,9 +136,9 @@ 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 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
-    public void setBaseMargin(float[][] baseMargin) throws XgboostError {
+    public void setBaseMargin(float[][] baseMargin) throws XGBoostError {
         float[] flattenMargin = flatten(baseMargin);
         setBaseMargin(flattenMargin);
     }
@@ -146,19 +146,19 @@ public class DMatrix {
     /**
      * Set group sizes of DMatrix (used for ranking)
      * @param group 
-     * @throws org.dmlc.xgboost4j.util.XgboostError 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
-    public void setGroup(int[] group) throws XgboostError {
+    public void setGroup(int[] group) throws XGBoostError {
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetGroup(handle, group));
     }
     
-    private float[] getFloatInfo(String field) throws XgboostError {
+    private float[] getFloatInfo(String field) throws XGBoostError {
         float[][] infos = new float[1][];
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixGetFloatInfo(handle, field, infos));
         return infos[0];
     }
     
-    private int[] getIntInfo(String field) throws XgboostError {
+    private int[] getIntInfo(String field) throws XGBoostError {
         int[][] infos = new int[1][];
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixGetUIntInfo(handle, field, infos));
         return infos[0];
@@ -167,27 +167,27 @@ public class DMatrix {
     /**
      * get label values
      * @return label
-     * @throws org.dmlc.xgboost4j.util.XgboostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError
      */
-    public float[] getLabel() throws XgboostError {
+    public float[] getLabel() throws XGBoostError {
         return getFloatInfo("label");
     }
     
     /**
      * get weight of the DMatrix
      * @return weights
-     * @throws org.dmlc.xgboost4j.util.XgboostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError
      */
-    public float[] getWeight() throws XgboostError {
+    public float[] getWeight() throws XGBoostError {
         return getFloatInfo("weight");
     }
     
     /**
      * get base margin of the DMatrix
      * @return base margin
-     * @throws org.dmlc.xgboost4j.util.XgboostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError
      */
-    public float[] getBaseMargin() throws XgboostError {
+    public float[] getBaseMargin() throws XGBoostError {
         return getFloatInfo("base_margin");
     }
     
@@ -195,9 +195,9 @@ public class DMatrix {
      * Slice the DMatrix and return a new DMatrix that only contains `rowIndex`.
      * @param rowIndex
      * @return sliced new DMatrix
-     * @throws org.dmlc.xgboost4j.util.XgboostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError
      */
-    public DMatrix slice(int[] rowIndex) throws XgboostError {
+    public DMatrix slice(int[] rowIndex) throws XGBoostError {
         long[] out = new long[1];
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixSliceDMatrix(handle, rowIndex, out));
         long sHandle = out[0];
@@ -208,9 +208,9 @@ 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
      */
-    public long rowNum() throws XgboostError {
+    public long rowNum() throws XGBoostError {
         long[] rowNum = new long[1];
         ErrorHandle.checkCall(XgboostJNI.XGDMatrixNumRow(handle,rowNum));
         return rowNum[0];
diff --git a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/CVPack.java b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/CVPack.java
index 33be48b53..a9b932f0d 100644
--- a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/CVPack.java
+++ b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/CVPack.java
@@ -37,9 +37,9 @@ 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
      */
-    public CVPack(DMatrix dtrain, DMatrix dtest, Iterable<Map.Entry<String, Object>> params) throws XgboostError {
+    public CVPack(DMatrix dtrain, DMatrix dtest, Iterable<Map.Entry<String, Object>> params) throws XGBoostError {
         dmats = new DMatrix[] {dtrain, dtest};
         booster = new Booster(params, dmats);
         names = new String[] {"train", "test"};
@@ -50,9 +50,9 @@ public class CVPack {
     /**
      * update one iteration
      * @param iter iteration num
-     * @throws org.dmlc.xgboost4j.util.XgboostError
+     * @throws org.dmlc.xgboost4j.util.XGBoostError
      */
-    public void update(int iter) throws XgboostError {
+    public void update(int iter) throws XGBoostError {
         booster.update(dtrain, iter);
     }
     
@@ -60,9 +60,9 @@ 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
      */
-    public void update(int iter, IObjective obj) throws XgboostError {
+    public void update(int iter, IObjective obj) throws XGBoostError {
         booster.update(dtrain, iter, obj);
     }
     
@@ -70,9 +70,9 @@ public class CVPack {
      * evaluation 
      * @param iter iteration num
      * @return 
-     * @throws org.dmlc.xgboost4j.util.XgboostError 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
-    public String eval(int iter) throws XgboostError {
+    public String eval(int iter) throws XGBoostError {
         return booster.evalSet(dmats, names, iter);
     }
     
@@ -81,9 +81,9 @@ public class CVPack {
      * @param iter iteration num
      * @param eval customized eval
      * @return 
-     * @throws org.dmlc.xgboost4j.util.XgboostError 
+     * @throws org.dmlc.xgboost4j.util.XGBoostError 
      */
-    public String eval(int iter, IEvaluation eval) throws XgboostError {
+    public String eval(int iter, IEvaluation eval) throws XGBoostError {
         return booster.evalSet(dmats, names, iter, eval);
     }
 }
diff --git a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/ErrorHandle.java b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/ErrorHandle.java
index 5093eb1db..688cd2719 100644
--- a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/ErrorHandle.java
+++ b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/ErrorHandle.java
@@ -40,11 +40,11 @@ public class ErrorHandle {
     /**
      * 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
      */
-    public static void checkCall(int ret) throws XgboostError {
+    public static void checkCall(int ret) throws XGBoostError {
         if(ret != 0) {
-            throw new XgboostError(XgboostJNI.XGBGetLastError());
+            throw new XGBoostError(XgboostJNI.XGBGetLastError());
         }
     }
 }
diff --git a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/Trainer.java b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/Trainer.java
index a81963da7..e5ac8502a 100644
--- a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/Trainer.java
+++ b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/Trainer.java
@@ -47,7 +47,7 @@ public class Trainer {
      * @return trained booster
      */
     public static Booster train(Iterable<Entry<String, Object>> params, DMatrix dtrain, int round, 
-            Iterable<Entry<String, DMatrix>> watchs, IObjective obj, IEvaluation eval) throws XgboostError {
+            Iterable<Entry<String, DMatrix>> watchs, IObjective obj, IEvaluation eval) throws XGBoostError {
         
         //collect eval matrixs
         String[] evalNames;
@@ -112,7 +112,7 @@ public class Trainer {
      * @param eval customized evaluation (set to null if not used)
      * @return evaluation history
      */
-    public static String[] crossValiation(Iterable<Entry<String, Object>> params, DMatrix data, int round, int nfold, String[] metrics, IObjective obj, IEvaluation eval) throws XgboostError {
+    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);
         String[] evalHist = new String[round];
         String[] results = new String[cvPacks.length];
@@ -149,7 +149,7 @@ public class Trainer {
      * @param evalMetrics Evaluation metrics
      * @return CV package array
      */
-    public static CVPack[] makeNFold(DMatrix data, int nfold, Iterable<Entry<String, Object>> params, String[] evalMetrics) throws XgboostError {
+    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());
         int step = samples.size()/nfold;
         int[] testSlice = new int[step];
diff --git a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/XgboostError.java b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/XGBoostError.java
similarity index 88%
rename from java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/XgboostError.java
rename to java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/XGBoostError.java
index 8dabcee4b..dc7a9a0b2 100644
--- a/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/XgboostError.java
+++ b/java/xgboost4j/src/main/java/org/dmlc/xgboost4j/util/XGBoostError.java
@@ -19,8 +19,8 @@ package org.dmlc.xgboost4j.util;
  * custom error class for xgboost
  * @author hzx
  */
-public class XgboostError extends Exception{
-    public XgboostError(String message) {
+public class XGBoostError extends Exception{
+    public XGBoostError(String message) {
         super(message);
     }
 }