Twin Support Vector Machine for Multiple Instance Learning Based on Bag Dissimilarities

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/aai/volume-2016/1269708/figures/1269708.fig.007a.svgz" name="1269708.fig.007a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Linear</td></tr><tr class="fig-image" id="b"><td><object data="https://static.hindawi.com/articles/aai/volume-2016/1269708/figures/1269708.fig.007b.svgz" name="1269708.fig.007b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Nonlinear</td></tr></table>

<div>Influence of parameters on the predictive accuracy of MIL-TWSVM (Minimum Hausdorff) on Fox dataset.</div>

Advances in Artificial Intelligence

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Figure 7

Figure 7: Twin Support Vector Machine for Multiple Instance Learning Based on Bag Dissimilarities 