コード例 #1
0
ファイル: DRFProgressPage.java プロジェクト: jmcclell/h2o
 @Override
 public boolean toHTML(StringBuilder sb) {
   Job jjob = Job.findJob(job_key);
   DRFModel m = UKV.get(jjob.dest());
   if (m != null) m.generateHTML("DRF Model", sb);
   else DocGen.HTML.paragraph(sb, "Pending...");
   return true;
 }
コード例 #2
0
ファイル: DRFModelAdaptTest.java プロジェクト: jamesliu/h2o
  void testModelAdaptation(String train, String test, PrepData dprep, boolean exactAdaptation) {
    DRFModel model = null;
    Frame frTest = null;
    Frame frTrain = null;
    Key trainKey = Key.make("train.hex");
    Key testKey = Key.make("test.hex");
    Frame[] frAdapted = null;
    try {
      // Prepare a simple model
      frTrain = parseFrame(trainKey, train);
      model = runDRF(frTrain, dprep);
      // Load test dataset - test data contains input columns matching train data,
      // BUT each input requires adaptation. Moreover, test data contains additional columns
      // containing correct value mapping.
      frTest = parseFrame(testKey, test);
      Assert.assertEquals(
          "TEST CONF ERROR: The test dataset should contain 2*<number of input columns>+1!",
          2 * (frTrain.numCols() - 1) + 1,
          frTest.numCols());
      // Adapt test dataset
      frAdapted = model.adapt(frTest, exactAdaptation); // do/do not perform translation to enums
      Assert.assertEquals("Adapt method should return two frames", 2, frAdapted.length);
      Assert.assertEquals(
          "Test expects that all columns in  test dataset has to be adapted",
          dprep.needAdaptation(frTrain),
          frAdapted[1].numCols());

      // Compare vectors
      Frame adaptedFrame = frAdapted[0];
      // System.err.println(frTest.toStringAll());
      // System.err.println(adaptedFrame.toStringAll());

      for (int av = 0; av < frTrain.numCols() - 1; av++) {
        int ev = av + frTrain.numCols();
        Vec actV = adaptedFrame.vecs()[av];
        Vec expV = frTest.vecs()[ev];
        Assert.assertEquals(
            "Different number of rows in test vectors", expV.length(), actV.length());
        for (long r = 0; r < expV.length(); r++) {
          if (expV.isNA(r))
            Assert.assertTrue(
                "Badly adapted vector - expected NA! Col: " + av + ", row: " + r, actV.isNA(r));
          else {
            Assert.assertTrue(
                "Badly adapted vector - expected value but get NA! Col: " + av + ", row: " + r,
                !actV.isNA(r));
            Assert.assertEquals(
                "Badly adapted vector - wrong values! Col: " + av + ", row: " + r,
                expV.at8(r),
                actV.at8(r));
          }
        }
      }

    } finally {
      // Test cleanup
      if (model != null) UKV.remove(model._selfKey);
      if (frTrain != null) frTrain.remove();
      UKV.remove(trainKey);
      if (frTest != null) frTest.remove();
      UKV.remove(testKey);
      // Remove adapted vectors which were saved into KV-store, rest of vectors are remove by
      // frTest.remove()
      if (frAdapted != null) frAdapted[1].remove();
    }
  }