[jvm-packages] create dmatrix with specified missing value (#1272)

* create dmatrix with specified missing value

* update dmlc-core

* support for predict method in spark package

repartitioning

work around

* add more elements to work around training set empty partition issue

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

@@ -118,6 +118,19 @@ public class DMatrix {
     handle = out[0];
   }
 
+  /**
+   * create DMatrix from dense matrix
+   * @param data data values
+   * @param nrow number of rows
+   * @param ncol number of columns
+   * @param missing the specified value to represent the missing value
+   */
+  public DMatrix(float[] data, int nrow, int ncol, float missing) throws XGBoostError {
+    long[] out = new long[1];
+    JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixCreateFromMat(data, nrow, ncol, missing, out));
+    handle = out[0];
+  }
+
   /**
    * used for DMatrix slice
    */

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

@@ -67,6 +67,19 @@ class DMatrix private[scala](private[scala] val jDMatrix: JDMatrix) {
     this(new JDMatrix(data, nrow, ncol))
   }
 
+  /**
+   * create DMatrix from dense matrix
+   *
+   * @param data data values
+   * @param nrow number of rows
+   * @param ncol number of columns
+   * @param missing the specified value to represent the missing value
+   */
+  @throws(classOf[XGBoostError])
+  def this(data: Array[Float], nrow: Int, ncol: Int, missing: Float) {
+    this(new JDMatrix(data, nrow, ncol, missing))
+  }
+
   /**
    * set label of dmatrix
    *

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

@@ -125,4 +125,34 @@ public class DMatrixTest {
 
     TestCase.assertTrue(Arrays.equals(weights, dmat0.getWeight()));
   }
+
+  @Test
+  public void testCreateFromDenseMatrixWithMissingValue() throws XGBoostError {
+    //create DMatrix from 10*5 dense matrix
+    int nrow = 10;
+    int ncol = 5;
+    float[] data0 = new float[nrow * ncol];
+    //put random nums
+    Random random = new Random();
+    for (int i = 0; i < nrow * ncol; i++) {
+      if (i % 10 == 0) {
+        data0[i] = -0.1f;
+      } else {
+        data0[i] = random.nextFloat();
+      }
+    }
+
+    //create label
+    float[] label0 = new float[nrow];
+    for (int i = 0; i < nrow; i++) {
+      label0[i] = random.nextFloat();
+    }
+
+    DMatrix dmat0 = new DMatrix(data0, nrow, ncol, -0.1f);
+    dmat0.setLabel(label0);
+
+    //check
+    TestCase.assertTrue(dmat0.rowNum() == 10);
+    TestCase.assertTrue(dmat0.getLabel().length == 10);
+  }
 }

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

@@ -82,4 +82,28 @@ class DMatrixSuite extends FunSuite {
     dmat0.setWeight(weights)
     assert(weights === dmat0.getWeight)
   }
+
+  test("create DMatrix from DenseMatrix with missing value") {
+    val nrow = 10
+    val ncol = 5
+    val data0 = new Array[Float](nrow * ncol)
+    // put random nums
+    for (i <- data0.indices) {
+      if (i % 10 == 0) {
+        data0(i) = -0.1f
+      } else {
+        data0(i) = Random.nextFloat()
+      }
+    }
+    // create label
+    val label0 = new Array[Float](nrow)
+    for (i <- label0.indices) {
+      label0(i) = Random.nextFloat()
+    }
+    val dmat0 = new DMatrix(data0, nrow, ncol, -0.1f)
+    dmat0.setLabel(label0)
+    // check
+    assert(dmat0.rowNum === 10)
+    assert(dmat0.getLabel.length === 10)
+  }
 }