Exact(4)
We used a kernel perceptron as a supervised learner [25] and an estimation of distribution algorithm for the estimate component [24].
For organisms with some known regulation edges as domain knowledge, they can be used as training examples to train a supervised learner, or be used to transform the existing method into a semi-supervised one [23].
The task of the supervised learner is to predict the value of the function for any valid input object after having seen a number of training examples.
Finally, the classification task of the supervised learner is to predict by using several paradigms the class of an unknown pattern after a training procedure based on a subset of samples.
Similar(56)
Differently, the derived term groups are then encoded as new features for the supervised learners in order to improve the coverage of lexical information.
Next best methods are supervised learners KNN and Gaussian NB.
First, our approach could not always defeat supervised learners as it is seen from Tables 3 and 5.
Unlike [15] in which we did not compare our method with other approaches, this work compares our proposed framework against other semi-supervised and supervised learners.
Some supervised learners at all levels, while others focused on a particular learner level.
AdaBoost (Freund and Schapire, 1997; Schapire et al., 1998) is a popular algorithm among a class of supervised learners called ensemble systems, which also includes RFs and Bagging.
In contrast, [15] utilized the off-the-shelf graph based semi-supervised learner, LabelSpreading method [24], without any further manipulation of the original approach.
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