Feature Selection in Decision Systems: A Mean-Variance Approach

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="268063.fig.002a" src="https://static.hindawi.com/articles/mpe/volume-2013/268063/figures/268063.fig.002a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>  Dependency</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="268063.fig.002b" src="https://static.hindawi.com/articles/mpe/volume-2013/268063/figures/268063.fig.002b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b> MI</td></tr></table></td></tr><tr class="fig-image" id="c"><td><img alt="268063.fig.002c" src="https://static.hindawi.com/articles/mpe/volume-2013/268063/figures/268063.fig.002c.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(c) </b>MVM</td></tr></table></td></tr></table>

<table> Comparison of convergence among three methods.</table>

Mathematical Problems in Engineering

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Figure 2: Feature Selection in Decision Systems: A Mean-Variance Approach 