"The classification was a supervised learning approach and, therefore, the class structure was
specified in advance by domain experts. The goal of this paper is to evaluate the degree of ambiguity
between two classes in the existing class structure via Euclidean distance. In this paper, Distinguishable
Distance Ratio (DDR) and Class Ambiguity Ratio (CAR) between two classes are proposed to indicate
the degree of the ambiguity between classes. The degree of class ambiguity between two classes is
expected to be high if the value of DDR is low and the value of CAR is high. The experimental
resources for class structure evaluation includes “Iris Plant,” “Wine Recognition” and “Glass
Identification,” and the values of DDR and CAR were found to reveal the degree of class ambiguity.
This work offers domain expertise an approach to examine the fitness of class structure, if necessary.
To our knowledge, we are the first to address the problem of the ambiguity of class structure"