adjust the API signature as well as the docs

jvm-packages/xgboost4j/src/main/java/ml/dmlc/xgboost4j/java/XGBoost.java

@@ -60,8 +60,8 @@ public class XGBoost {
   /**
    * Train a booster with given parameters.
    *
-   * @param params Booster params.
    * @param dtrain Data to be trained.
+   * @param params Booster params.
    * @param round  Number of boosting iterations.
    * @param watches a group of items to be evaluated during training, this allows user to watch
    *               performance on the validation set.
@@ -70,11 +70,13 @@ public class XGBoost {
    * @return trained booster
    * @throws XGBoostError native error
    */
-  public static Booster train(Map<String, Object> params,
-                              DMatrix dtrain, int round,
-                              Map<String, DMatrix> watches,
-                              IObjective obj,
-                              IEvaluation eval) throws XGBoostError {
+  public static Booster train(
+      DMatrix dtrain,
+      Map<String, Object> params,
+      int round,
+      Map<String, DMatrix> watches,
+      IObjective obj,
+      IEvaluation eval) throws XGBoostError {
 
     //collect eval matrixs
     String[] evalNames;
@@ -139,8 +141,8 @@ public class XGBoost {
   /**
    * Cross-validation with given parameters.
    *
-   * @param params  Booster params.
    * @param data    Data to be trained.
+   * @param params  Booster params.
    * @param round   Number of boosting iterations.
    * @param nfold   Number of folds in CV.
    * @param metrics Evaluation metrics to be watched in CV.
@@ -150,8 +152,8 @@ public class XGBoost {
    * @throws XGBoostError native error
    */
   public static String[] crossValidation(
-      Map<String, Object> params,
       DMatrix data,
+      Map<String, Object> params,
       int round,
       int nfold,
       String[] metrics,

jvm-packages/xgboost4j/src/main/scala/ml/dmlc/xgboost4j/scala/XGBoost.scala

@@ -28,8 +28,8 @@ object XGBoost {
   /**
     * Train a booster given parameters.
     *
-    * @param params  Parameters.
     * @param dtrain  Data to be trained.
+    * @param params  Parameters.
     * @param round   Number of boosting iterations.
     * @param watches a group of items to be evaluated during training, this allows user to watch
     *                performance on the validation set.
@@ -39,8 +39,8 @@ object XGBoost {
     */
   @throws(classOf[XGBoostError])
   def train(
-      params: Map[String, Any],
       dtrain: DMatrix,
+      params: Map[String, Any],
       round: Int,
       watches: Map[String, DMatrix] = Map[String, DMatrix](),
       obj: ObjectiveTrait = null,
@@ -49,10 +49,11 @@ object XGBoost {
 
     val jWatches = watches.map{case (name, matrix) => (name, matrix.jDMatrix)}
     val xgboostInJava = JXGBoost.train(
+      dtrain.jDMatrix,
       params.map{
         case (key: String, value) => (key, value.toString)
       }.toMap[String, AnyRef].asJava,
-      dtrain.jDMatrix, round, jWatches.asJava,
+      round, jWatches.asJava,
       obj, eval)
     new Booster(xgboostInJava)
   }
@@ -60,8 +61,8 @@ object XGBoost {
   /**
     * Cross-validation with given parameters.
     *
-    * @param params  Booster params.
     * @param data    Data to be trained.
+    * @param params  Booster params.
     * @param round   Number of boosting iterations.
     * @param nfold   Number of folds in CV.
     * @param metrics Evaluation metrics to be watched in CV.
@@ -71,17 +72,17 @@ object XGBoost {
     */
   @throws(classOf[XGBoostError])
   def crossValidation(
-      params: Map[String, Any],
       data: DMatrix,
+      params: Map[String, Any],
       round: Int,
       nfold: Int = 5,
       metrics: Array[String] = null,
       obj: ObjectiveTrait = null,
       eval: EvalTrait = null): Array[String] = {
-    JXGBoost.crossValidation(params.map{
-      case (key: String, value) => (key, value.toString)
-    }.toMap[String, AnyRef].asJava,
-      data.jDMatrix, round, nfold, metrics, obj, eval)
+    JXGBoost.crossValidation(
+      data.jDMatrix, params.map{ case (key: String, value) => (key, value.toString)}.
+        toMap[String, AnyRef].asJava,
+      round, nfold, metrics, obj, eval)
   }
 
   /**

jvm-packages/xgboost4j/src/test/java/ml/dmlc/xgboost4j/java/BoosterImplTest.java

@@ -94,7 +94,7 @@ public class BoosterImplTest {
     int round = 5;
 
     //train a boost model
-    return XGBoost.train(paramMap, trainMat, round, watches, null, null);
+    return XGBoost.train(trainMat, paramMap, round, watches, null, null);
   }
 
   @Test
@@ -177,6 +177,6 @@ public class BoosterImplTest {
     //do 5-fold cross validation
     int round = 2;
     int nfold = 5;
-    String[] evalHist = XGBoost.crossValidation(param, trainMat, round, nfold, null, null, null);
+    String[] evalHist = XGBoost.crossValidation(trainMat, param, round, nfold, null, null, null);
   }
 }

jvm-packages/xgboost4j/src/test/scala/ml/dmlc/xgboost4j/scala/ScalaBoosterImplSuite.scala

@@ -74,7 +74,7 @@ class ScalaBoosterImplSuite extends FunSuite {
     val watches = List("train" -> trainMat, "test" -> testMat).toMap
 
     val round = 2
-    XGBoost.train(paramMap, trainMat, round, watches, null, null)
+    XGBoost.train(trainMat, paramMap, round, watches, null, null)
   }
 
   test("basic operation of booster") {
@@ -126,6 +126,6 @@ class ScalaBoosterImplSuite extends FunSuite {
       "objective" -> "binary:logistic", "gamma" -> "1.0", "eval_metric" -> "error").toMap
     val round = 2
     val nfold = 5
-    XGBoost.crossValidation(params, trainMat, round, nfold, null, null, null)
+    XGBoost.crossValidation(trainMat, params, round, nfold, null, null, null)
   }
 }