This paper presents a new fuzziness measure for rough sets. Fuzziness measures for rough sets may be employed to describe the inconsistency of a decision table. The definition of the fuzziness of a rough set proposed by Chakrabarty et al. has two drawbacks. The first is that the fuzziness of a rough set may not be unique. The second is that the fuzziness of a rough set with a large boundary may...

The Open Geospatial Consortium (OGC) Geography Markup Language (GML) explicitly represents geographical spatial knowledge in text mode. All kinds of fuzzy problems will inevitably be encountered in spatial knowledge expression. Especially for those expressions in text mode, this fuzziness will be broader. Describing and representing fuzziness in GML seems necessary. Three kinds of fuzziness in ...

This paper investigates a relationship between the fuzziness of a classifier and the misclassification rate of the classifier on a group of samples. For a given trained classifier that outputs a membership vector, we demonstrate experimentally that samples with higher fuzziness outputted by the classifier mean a bigger risk of misclassification. We then propose a fuzziness category based divide...

To measure the fuzziness of fuzzy sets, this paper introduces a distance-based and a fuzzy entropybased measurements. Then these measurements are generalized to measure the fuzziness of fuzzy partition, namely partition fuzziness. According to the relationship between the validity of fuzzy partition and its partition fuzziness, a family of cluster validity functions is proposed based on the mod...

The “Double Fuzzy Point” rule representation opens a new dimension for expressing changes of fuzziness in fuzzy rule-based systems. In the case of standard “Fuzzy Point” rule representations, it is difficult to describe fuzzy functions in which crisp observations are required to have fuzzy conclusions, or in which an increase in the fuzziness of observations leads to reduced fuzziness in conclu...