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Here the NB classifier was used as a baseline method.
To avoid this issue, a baseline method based on a naive Bayes classifier is proposed.
A famous transfer learning method called KMM [10] is also used here as a baseline method.
A baseline method is tested using an SVM classifier trained only with the labeled target data.
A baseline method is tested where an SVM classifier is trained on the source domain.
It was proposed in [5] as a baseline method for comparison purposes.
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Since PITA does not use conservation, we next tested if PITA outperformed a simple baseline method: a naïve seed-match procedure that predicts all sequences reverse-complementary to bases 1 7 or 2 8 from the 5' end of a mature miRNA as a target site.
Our first method, acting as a naïve baseline method, predicts a stated connection between every pair of brain region mentions (Jensen et al., 2006).
We evaluate the performance of a representative set of existing methods for predicting SDPs from a MSA divided into specificity groups against a simple, baseline method.
Experimental results show that the classification method can outperform a probabilistic baseline method, which is calculated by the original graph-based dependency parser.
We have presented results comparing INTREPID with two of the leading methods in functional residue prediction that make use of sequence information only ET and ConSurf and with a simple baseline method that computes the JS divergence between the amino acid distribution at a position and a background distribution (Global-JS).
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