The paper presents a feature selection method based on both cluster analysis and possibility functions. The proposed method is especially valuable whenever the sample of points is so small or the number of features is so large that the probabilistic approach is powerless. The procedure devised by the authors to perform the feature selection is presented with clarity and concision. Results obtained by applying the method to a set of biomedical data are provided. The method also seems suitable for gamma-ray astronomy applications.