Package org.apache.mahout.math

Examples of org.apache.mahout.math.DenseMatrix.viewColumn()

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    values[1][1] = 0.0;
    values[2][2] = 0.0;

    Matrix dataset = new DenseMatrix(values);
    this.trainer.train(labelset, dataset);
    assertFalse(this.trainer.getModel().classify(dataset.viewColumn(3)));
    assertTrue(this.trainer.getModel().classify(dataset.viewColumn(0)));
  }

}
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    values[2][2] = 0.0;

    Matrix dataset = new DenseMatrix(values);
    this.trainer.train(labelset, dataset);
    assertFalse(this.trainer.getModel().classify(dataset.viewColumn(3)));
    assertTrue(this.trainer.getModel().classify(dataset.viewColumn(0)));
  }

}
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    values[1][1] = 0.0;
    values[2][2] = 0.0;

    Matrix dataset = new DenseMatrix(values);
    trainer.train(labelset, dataset);
    assertTrue(trainer.getModel().classify(dataset.viewColumn(3)));
    assertFalse(trainer.getModel().classify(dataset.viewColumn(0)));
  }

}
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    values[2][2] = 0.0;

    Matrix dataset = new DenseMatrix(values);
    trainer.train(labelset, dataset);
    assertTrue(trainer.getModel().classify(dataset.viewColumn(3)));
    assertFalse(trainer.getModel().classify(dataset.viewColumn(0)));
  }

}
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    values[1][1] = 0.0;
    values[2][2] = 0.0;

    Matrix dataset = new DenseMatrix(values);
    trainer.train(labelset, dataset);
    assertTrue(trainer.getModel().classify(dataset.viewColumn(3)));
    assertFalse(trainer.getModel().classify(dataset.viewColumn(0)));
  }

}
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    values[2][2] = 0.0;

    Matrix dataset = new DenseMatrix(values);
    trainer.train(labelset, dataset);
    assertTrue(trainer.getModel().classify(dataset.viewColumn(3)));
    assertFalse(trainer.getModel().classify(dataset.viewColumn(0)));
  }

}
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    values[1][1] = 0.0;
    values[2][2] = 0.0;

    Matrix dataset = new DenseMatrix(values);
    this.trainer.train(labelset, dataset);
    assertFalse(this.trainer.getModel().classify(dataset.viewColumn(3)));
    assertTrue(this.trainer.getModel().classify(dataset.viewColumn(0)));
  }

}
View Full Code Here
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    values[2][2] = 0.0;

    Matrix dataset = new DenseMatrix(values);
    this.trainer.train(labelset, dataset);
    assertFalse(this.trainer.getModel().classify(dataset.viewColumn(3)));
    assertTrue(this.trainer.getModel().classify(dataset.viewColumn(0)));
  }

}
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