A Novel Method for Functional Annotation Prediction Based on Combination of Classification Methods

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="542824.fig.005a" src="https://static.hindawi.com/articles/tswj/volume-2014/542824/figures/542824.fig.005a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>The error rate of employing adaboosting under different conditions at randomly selected GO terms</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="542824.fig.005b" src="https://static.hindawi.com/articles/tswj/volume-2014/542824/figures/542824.fig.005b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>The error rate of employing SMO under different conditions at randomly selected GO terms</td></tr></table></td></tr><tr class="fig-image" id="c"><td><img alt="542824.fig.005c" src="https://static.hindawi.com/articles/tswj/volume-2014/542824/figures/542824.fig.005c.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(c) </b>The error rate of employing SVM under different conditions at randomly selected GO terms</td></tr></table></td></tr></table>

<table>The error rate of three different techniques.</table>

The Scientific World Journal

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Figure 5

Figure 5: A Novel Method for Functional Annotation Prediction Based on Combination of Classification Methods 