A New Method to Measure the Similarity between Features in Machine Learning Using the Triangular Fuzzy Number

In this paper, we present a new method to measure the similarity between features using fuzzy numbers. The proposed method uses the concept of geometry to calculate the degree of similarity between triangular fuzzy numbers defined on the features. We also prove some properties of the proposed similarity measure and use different data sets to compare the proposed method with existing methods. In the feature selection methods, the proposed similarity measure compared with other fuzzy similarity measures can be more efficient.