water.fvec.Frame.lastVecName()方法的使用及代码示例

x33g5p2x  于2022-01-19 转载在 其他  
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本文整理了Java中water.fvec.Frame.lastVecName()方法的一些代码示例，展示了Frame.lastVecName()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Frame.lastVecName()方法的具体详情如下：
包路径：water.fvec.Frame
类名称：Frame
方法名：lastVecName

Frame.lastVecName介绍

暂无

代码示例

代码示例来源：origin: h2oai/h2o-3

@Test
public void testMiniBatch50() {
 Frame tfr = null;
 DeepLearningModel dl = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  DeepLearningParameters parms = new DeepLearningParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._reproducible = true;
  parms._hidden = new int[]{20,20};
  parms._seed = 0xdecaf;
  parms._mini_batch_size = 50;
  dl = new DeepLearning(parms).trainModel().get();
  Assert.assertEquals(12.938076268040659,dl._output._training_metrics._MSE,1e-6);
 } finally {
  if (tfr != null) tfr.delete();
  if (dl != null) dl.deleteCrossValidationModels();
  if (dl != null) dl.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testCatEncodingCV() {
 for (Model.Parameters.CategoricalEncodingScheme c : Model.Parameters.CategoricalEncodingScheme.values()) {
  if (c != Model.Parameters.CategoricalEncodingScheme.AUTO) continue;
  Frame tfr = null;
  GBMModel gbm = null;
  try {
   tfr = parse_test_file("./smalldata/junit/weather.csv");
   GBMModel.GBMParameters parms = new GBMModel.GBMParameters();
   parms._train = tfr._key;
   parms._response_column = tfr.lastVecName();
   parms._ntrees = 5;
   parms._categorical_encoding = c;
   parms._nfolds = 3;
   gbm = new GBM(parms).trainModel().get();
  } finally {
   if (tfr != null) tfr.delete();
   if (gbm != null) gbm.deleteCrossValidationModels();
   if (gbm != null) gbm.delete();
  }
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testMiniBatch1() {
 Frame tfr = null;
 DeepLearningModel dl = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  DeepLearningParameters parms = new DeepLearningParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._reproducible = true;
  parms._hidden = new int[]{20,20};
  parms._seed = 0xdecaf;
  parms._mini_batch_size = 1;
  dl = new DeepLearning(parms).trainModel().get();
  Assert.assertEquals(12.938076268040659,dl._output._training_metrics._MSE,1e-6);
 } finally {
  if (tfr != null) tfr.delete();
  if (dl != null) dl.deleteCrossValidationModels();
  if (dl != null) dl.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testHuber() {
 Frame tfr = null;
 DeepLearningModel dl = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  DeepLearningParameters parms = new DeepLearningParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._reproducible = true;
  parms._hidden = new int[]{20,20};
  parms._seed = 0xdecaf;
  parms._distribution = huber;
  dl = new DeepLearning(parms).trainModel().get();
  Assert.assertEquals(6.4964976811,((ModelMetricsRegression)dl._output._training_metrics)._mean_residual_deviance,1e-5);
 } finally {
  if (tfr != null) tfr.delete();
  if (dl != null) dl.deleteCrossValidationModels();
  if (dl != null) dl.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testGaussian() {
 Frame tfr = null;
 GBMModel gbm = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  GBMModel.GBMParameters parms = new GBMModel.GBMParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._seed = 0xdecaf;
  parms._distribution = gaussian;
  gbm = new GBM(parms).trainModel().get();
  Assert.assertEquals(2.9423857564,((ModelMetricsRegression) gbm._output._training_metrics)._MSE,1e-5);
  Assert.assertEquals(2.9423857564,((ModelMetricsRegression) gbm._output._training_metrics)._mean_residual_deviance,1e-5);
 } finally {
  if (tfr != null) tfr.delete();
  if (gbm != null) gbm.deleteCrossValidationModels();
  if (gbm != null) gbm.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testGaussian() {
 Frame tfr = null;
 DeepLearningModel dl = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  DeepLearningParameters parms = new DeepLearningParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._reproducible = true;
  parms._hidden = new int[]{20,20};
  parms._seed = 0xdecaf;
  parms._distribution = gaussian;
  dl = new DeepLearning(parms).trainModel().get();
  Assert.assertEquals(12.93808 /*MSE*/,((ModelMetricsRegression)dl._output._training_metrics)._mean_residual_deviance,1e-5);
  Assert.assertEquals(12.93808 /*MSE*/,((ModelMetricsRegression)dl._output._training_metrics)._MSE,1e-5);
 } finally {
  if (tfr != null) tfr.delete();
  if (dl != null) dl.deleteCrossValidationModels();
  if (dl != null) dl.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testLaplace() {
 Frame tfr = null;
 GBMModel gbm = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  GBMModel.GBMParameters parms = new GBMModel.GBMParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._seed = 0xdecaf;
  parms._distribution = laplace;
  gbm = new GBM(parms).trainModel().get();
  Assert.assertEquals(8.05716257,((ModelMetricsRegression)gbm._output._training_metrics)._MSE,1e-5);
  Assert.assertEquals(1.42298/*MAE*/,((ModelMetricsRegression)gbm._output._training_metrics)._mean_residual_deviance,1e-5);
 } finally {
  if (tfr != null) tfr.delete();
  if (gbm != null) gbm.deleteCrossValidationModels();
  if (gbm != null) gbm.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testHuberNoise() {
 Frame tfr = null;
 GBMModel gbm = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  GBMModel.GBMParameters parms = new GBMModel.GBMParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._seed = 0xdecaf;
  parms._distribution = huber;
  parms._huber_alpha = 0.9; //that's the default
  parms._pred_noise_bandwidth = 0.2;
  gbm = new GBM(parms).trainModel().get();
  Assert.assertEquals(4.8056900203,((ModelMetricsRegression)gbm._output._training_metrics)._MSE,1e-5);
  Assert.assertEquals(2.0080997,((ModelMetricsRegression) gbm._output._training_metrics)._mean_residual_deviance,1e-4);
 } finally {
  if (tfr != null) tfr.delete();
  if (gbm != null) gbm.deleteCrossValidationModels();
  if (gbm != null) gbm.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testHuber() {
 Frame tfr = null;
 GBMModel gbm = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  GBMModel.GBMParameters parms = new GBMModel.GBMParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._seed = 0xdecaf;
  parms._distribution = huber;
  parms._huber_alpha = 0.9; //that's the default
  gbm = new GBM(parms).trainModel().get();
  Assert.assertEquals(4.447062185,((ModelMetricsRegression)gbm._output._training_metrics)._MSE,1e-5);
  Assert.assertEquals(1.962926332,((ModelMetricsRegression) gbm._output._training_metrics)._mean_residual_deviance,1e-4);
 } finally {
  if (tfr != null) tfr.delete();
  if (gbm != null) gbm.deleteCrossValidationModels();
  if (gbm != null) gbm.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testCrossValidation() {
 Frame tfr = null;
 DeepLearningModel dl = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  DeepLearningParameters parms = new DeepLearningParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._reproducible = true;
  parms._hidden = new int[]{20,20};
  parms._seed = 0xdecaf;
  parms._nfolds = 4;
  dl = new DeepLearning(parms).trainModel().get();
  Assert.assertEquals(12.959355363801334,dl._output._training_metrics._MSE,1e-6);
  Assert.assertEquals(17.296871012606317,dl._output._cross_validation_metrics._MSE,1e-6);
 } finally {
  if (tfr != null) tfr.delete();
  if (dl != null) dl.deleteCrossValidationModels();
  if (dl != null) dl.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testHuberDeltaLarge() {
 Frame tfr = null;
 GBMModel gbm = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  GBMModel.GBMParameters parms = new GBMModel.GBMParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._seed = 0xdecaf;
  parms._distribution = huber;
  parms._huber_alpha = 1; // nothing is an outlier - same as gaussian
  gbm = new GBM(parms).trainModel().get();
  Assert.assertEquals(2.9423857564,((ModelMetricsRegression) gbm._output._training_metrics)._MSE,1e-2);
  // huber loss with delta -> max(error) goes to MSE
  Assert.assertEquals(2.9423857564,((ModelMetricsRegression) gbm._output._training_metrics)._mean_residual_deviance,1e-2);
 } finally {
  if (tfr != null) tfr.delete();
  if (gbm != null) gbm.deleteCrossValidationModels();
  if (gbm != null) gbm.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testLaplace() {
 Frame tfr = null;
 DeepLearningModel dl = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  DeepLearningParameters parms = new DeepLearningParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._reproducible = true;
  parms._hidden = new int[]{20,20};
  parms._seed = 0xdecaf;
  parms._distribution = laplace;
  dl = new DeepLearning(parms).trainModel().get();
  Assert.assertEquals(2.31398/*MAE*/,((ModelMetricsRegression)dl._output._training_metrics)._mean_residual_deviance,1e-5);
  Assert.assertEquals(14.889,((ModelMetricsRegression)dl._output._training_metrics)._MSE,1e-3);
 } finally {
  if (tfr != null) tfr.delete();
  if (dl != null) dl.deleteCrossValidationModels();
  if (dl != null) dl.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testHuberDeltaLarge() {
 Frame tfr = null;
 DeepLearningModel dl = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  DeepLearningParameters parms = new DeepLearningParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._reproducible = true;
  parms._hidden = new int[]{20,20};
  parms._seed = 0xdecaf;
  parms._distribution = huber;
  parms._huber_alpha = 1; //just like gaussian
  dl = new DeepLearning(parms).trainModel().get();
  Assert.assertEquals(12.93808 /*MSE*/,((ModelMetricsRegression)dl._output._training_metrics)._mean_residual_deviance,0.7);
  Assert.assertEquals(12.93808 /*MSE*/,((ModelMetricsRegression)dl._output._training_metrics)._MSE,0.7);
 } finally {
  if (tfr != null) tfr.delete();
  if (dl != null) dl.deleteCrossValidationModels();
  if (dl != null) dl.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

@Test
public void testHuberDeltaTiny() {
 Frame tfr = null;
 GBMModel gbm = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  GBMModel.GBMParameters parms = new GBMModel.GBMParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._seed = 0xdecaf;
  parms._distribution = huber;
  parms._huber_alpha = 1e-2; //everything is an outlier and we should get laplace loss
  gbm = new GBM(parms).trainModel().get();
  Assert.assertEquals(8.05716257,((ModelMetricsRegression)gbm._output._training_metrics)._MSE,0.3);
  // Huber loss can be derived from MAE since no obs weights
  double delta = 0.0047234; //hardcoded from output
  double MAE = 1.42298; //see laplace above
  Assert.assertEquals((2*MAE-delta)*delta,((ModelMetricsRegression)gbm._output._training_metrics)._mean_residual_deviance,1e-1);
 } finally {
  if (tfr != null) tfr.delete();
  if (gbm != null) gbm.deleteCrossValidationModels();
  if (gbm != null) gbm.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

parms._response_column = tfr.lastVecName();
parms._activation = DeepLearningParameters.Activation.Tanh;
parms._reproducible = true;
parms._response_column = tfr.lastVecName();
parms._activation = DeepLearningParameters.Activation.Tanh;
parms._reproducible = true;

代码示例来源：origin: h2oai/h2o-3

@Test
public void testHuberDeltaTiny() {
 Frame tfr = null;
 DeepLearningModel dl = null;
 try {
  tfr = parse_test_file("./smalldata/gbm_test/BostonHousing.csv");
  DeepLearningParameters parms = new DeepLearningParameters();
  parms._train = tfr._key;
  parms._response_column = tfr.lastVecName();
  parms._reproducible = true;
  parms._hidden = new int[]{20,20};
  parms._seed = 0xdecaf;
  parms._distribution = huber;
  parms._huber_alpha = 1e-2;
  // more like Laplace, but different slope and different prefactor -> so can't compare deviance 1:1
  dl = new DeepLearning(parms).trainModel().get();
  double delta = 0.011996;
  // can compute huber loss from MAE since no obs weights
  Assert.assertEquals((2*2.31398/*MAE*/-delta)*delta,((ModelMetricsRegression)dl._output._training_metrics)._mean_residual_deviance,2e-2);
  Assert.assertEquals(19.856,((ModelMetricsRegression)dl._output._training_metrics)._MSE,1e-3);
 } finally {
  if (tfr != null) tfr.delete();
  if (dl != null) dl.deleteCrossValidationModels();
  if (dl != null) dl.delete();
 }
}

代码示例来源：origin: h2oai/h2o-3

GBMModel.GBMParameters parms = new GBMModel.GBMParameters();
parms._train = tfr._key;
String resp = tfr.lastVecName();
if (dist==modified_huber || dist==bernoulli || dist==multinomial) {
 resp = dist==multinomial?"rad":"chas";

代码示例来源：origin: h2oai/h2o-3

GLMModel.GLMParameters parms = new GLMModel.GLMParameters();
parms._train = tfr._key;
String resp = tfr.lastVecName();
if (fam==Family.binomial || fam==Family.multinomial) {
 resp = fam==Family.multinomial?"rad":"chas";

代码示例来源：origin: h2oai/h2o-3

@Test
public void testCatEncoding() {
 for (Model.Parameters.CategoricalEncodingScheme c : Model.Parameters.CategoricalEncodingScheme.values()) {
  if (c != Model.Parameters.CategoricalEncodingScheme.AUTO) continue;
  Frame tfr = null;
  GBMModel gbm = null;
  Frame fr2 = null;
  try {
   tfr = parse_test_file("./smalldata/junit/weather.csv");
   GBMModel.GBMParameters parms = new GBMModel.GBMParameters();
   parms._train = tfr._key;
   parms._response_column = tfr.lastVecName();
   parms._ntrees = 5;
   parms._categorical_encoding = c;
   gbm = new GBM(parms).trainModel().get();
   // Done building model; produce a score column with predictions
   fr2 = gbm.score(tfr);
   // Build a POJO, validate same results
   Assert.assertTrue(gbm.testJavaScoring(tfr,fr2,1e-15));
  } finally {
   if (tfr != null) tfr.delete();
   if (fr2 != null) fr2.delete();
   if (gbm != null) gbm.deleteCrossValidationModels();
   if (gbm != null) gbm.delete();
  }
 }
}

代码示例来源：origin: h2oai/h2o-3

parms._response_column = tfr.lastVecName();
parms._activation = DeepLearningParameters.Activation.Tanh;
parms._reproducible = true;
parms._response_column = tfr.lastVecName();
parms._activation = DeepLearningParameters.Activation.Tanh;
parms._reproducible = true;

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