Gene Selection in Binary Classification Problems Within Functional Genomics Experiments via Robust Fisher Score
This study proposes a supervised feature selection technique for classification in high dimensional binary class problems by adding robustness in the conventional Fisher Score.The proposed method utilizes the more robust measure of location i.e.the Median and measure of dispersion known as Rousseeuw and Croux statistic ( $Q_{n}$ ).Initially minimum