TY - GEN
T1 - A new pseudo-metric for fuzzy sets
AU - Kovacs, Laszlo
AU - Ratsaby, Joel
PY - 2014
Y1 - 2014
N2 - A new distance function for fuzzy sets is introduced. It is based on the descriptive complexity, that is, the number of bits (on average) that are needed to describe an element in the symmetric difference of the two sets. The value of the distance gives the amount of additional information needed to describe either one of the two sets when the other is known. We prove that the distance function is a pseudo-metric, namely, it is non-negative, symmetric, it equals zero if the sets are identical and it satisfies the triangle inequality.
AB - A new distance function for fuzzy sets is introduced. It is based on the descriptive complexity, that is, the number of bits (on average) that are needed to describe an element in the symmetric difference of the two sets. The value of the distance gives the amount of additional information needed to describe either one of the two sets when the other is known. We prove that the distance function is a pseudo-metric, namely, it is non-negative, symmetric, it equals zero if the sets are identical and it satisfies the triangle inequality.
KW - Fuzzy sets
KW - descriptive complexity
KW - distance
KW - entropy
KW - triangle-inequality
UR - https://www.scopus.com/pages/publications/84902584377
U2 - 10.1007/978-3-319-07173-2_19
DO - 10.1007/978-3-319-07173-2_19
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AN - SCOPUS:84902584377
SN - 9783319071725
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 205
EP - 216
BT - Artificial Intelligence and Soft Computing - 13th International Conference, ICAISC 2014, Proceedings
T2 - 13th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2014
Y2 - 1 June 2014 through 5 June 2014
ER -