Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="314728.fig.009a" src="https://static.hindawi.com/articles/tswj/volume-2014/314728/figures/314728.fig.009a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Experiment 1</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="314728.fig.009b" src="https://static.hindawi.com/articles/tswj/volume-2014/314728/figures/314728.fig.009b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Experiment 2</td></tr></table></td></tr><tr class="fig-image" id="c"><td><img alt="314728.fig.009c" src="https://static.hindawi.com/articles/tswj/volume-2014/314728/figures/314728.fig.009c.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(c) </b>Experiment 12</td></tr></table></td></tr></table>

<table>Optimal Pareto fronts for German Credit data (10 runs).</table>

The Scientific World Journal

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Figure 9

Figure 9: Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data 