Figure 1
From: Feature weight estimation for gene selection: a local hyperlinear learning approach
Experiments on the Fermat’s Spiral problem. (a) The Spiral consists of two classes, each having 200 samples labeled by different colors; Boxplot results after LHR, I-RELIEF and LOGO through five classifiers on (a), degraded by noise features whose dimension extending from 0 to 10000. Two criteria of 10-fold CV (b) and LOOCV (c) are used to evaluate the performance of the feature selection methods. The result after various classifier is marked in red circle. The averaged values were connected to highlight the different performance.