Package org.apache.hama.commons.math

Examples of org.apache.hama.commons.math.DenseDoubleVector.slice()

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    double relativeError = 0;
    for (int i = 0; i < instances.length; ++i) {
      DoubleVector test = new DenseDoubleVector(instances[i]);
      double expected = test.get(test.getDimension() - 1);
      test = test.slice(test.getDimension() - 1);
      double actual = regression.getOutput(test).get(0);
      relativeError += Math.abs((expected - actual) / expected);
    }

    relativeError /= instances.length;
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    double relativeError = 0.0;
    // calculate the error on test instance
    for (double[] testInstance : testInstances) {
      DoubleVector instance = new DenseDoubleVector(testInstance);
      double expected = instance.get(instance.getDimension() - 1);
      instance = instance.slice(instance.getDimension() - 1);
      double actual = regression.getOutput(instance).get(0);
      if (expected == 0) {
        expected = 0.0000001;
      }
      relativeError += Math.abs((expected - actual) / expected);
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    double errorRate = 0;
    // calculate the error on test instance
    for (double[] testInstance : testInstances) {
      DoubleVector instance = new DenseDoubleVector(testInstance);
      double expected = instance.get(instance.getDimension() - 1);
      DoubleVector features = instance.slice(instance.getDimension() - 1);
      double actual = regression.getOutput(features).get(0);
      if (actual < 0.5 && expected >= 0.5 || actual >= 0.5 && expected < 0.5) {
        ++errorRate;
      }
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    double errorRate = 0;
    // calculate the error on test instance
    for (double[] testInstance : testInstances) {
      DoubleVector instance = new DenseDoubleVector(testInstance);
      double expected = instance.get(instance.getDimension() - 1);
      instance = instance.slice(instance.getDimension() - 1);
      double actual = ann.getOutput(instance).get(0);
      if (actual < 0.5 && expected >= 0.5 || actual >= 0.5 && expected < 0.5) {
        ++errorRate;
      }
    }
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    double errorRate = 0;
    // calculate the error on test instance
    for (double[] testInstance : testInstances) {
      DoubleVector instance = new DenseDoubleVector(testInstance);
      double expected = instance.get(instance.getDimension() - 1);
      instance = instance.slice(instance.getDimension() - 1);
      double actual = ann.getOutput(instance).get(0);
      if (actual < 0.5 && expected >= 0.5 || actual >= 0.5 && expected < 0.5) {
        ++errorRate;
      }
    }
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    double errorRate = 0;
    // calculate the error on test instance
    for (double[] testInstance : testInstances) {
      DoubleVector instance = new DenseDoubleVector(testInstance);
      double expected = instance.get(instance.getDimension() - 1);
      instance = instance.slice(instance.getDimension() - 1);
      instance = featureTransformer.transform(instance);
      double actual = ann.getOutput(instance).get(0);
      if (actual < 0.5 && expected >= 0.5 || actual >= 0.5 && expected < 0.5) {
        ++errorRate;
      }
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