<ul><li>Expressive evaluation metrics are indispensable for informative experiments in all areas, and while several metrics are established in some areas, in others, such as feature selection, only indirect or otherwise limited evaluation metrics are found.</li><li>In this paper, the authors propose a novel evaluation metric to address several problems of its predecessors and allow for flexible and reliable evaluation of feature selection algorithms.</li><li>The proposed metric is a dynamic metric with two properties that can be used to evaluate both the performance and the stability of a feature selection algorithm.</li><li>Empirical experiments are conducted to illustrate the use of the proposed metric in the successful evaluation of feature selection algorithms, and a comparison and analysis are provided to show the different aspects involved in the evaluation.</li></ul>

FSDEM: Feature Selection Dynamic Evaluation Metric

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