TY - GEN
T1 - Fuzzy co-clustering induced by q-multinomial mixture models
AU - Kanzawa, Yuchi
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Number 15K00348.
PY - 2017/8/23
Y1 - 2017/8/23
N2 - In this study, a new fuzzy co-clusterins algorithm based on a q-multinomial mixture model is proposed. A conventional fuzzy co-clustering model was constructed by fuzzifying a multinomial mixture model (MMM) via regularizing Kullback-Leibler divergence appearing in a pseudo likelihood of an MMM. Furthermore, a q-multinomial distribution was formulated, which acts as the Tsallis statistical counter for multinomial distributions in standard statistics. The proposed algorithm is constructed by fuzzifying a q-multinomial mixture model, by means of regularizing q-divergence appearing in a pseudo likelihood of the model. The proposed algorithm not only reduces into the q-multinomial mixture model, but also reduces into conventional fuzzy co-clustering models with specified sets of parameter values. In numerical experiments, the properties of the membership of the proposed method are observed.
AB - In this study, a new fuzzy co-clusterins algorithm based on a q-multinomial mixture model is proposed. A conventional fuzzy co-clustering model was constructed by fuzzifying a multinomial mixture model (MMM) via regularizing Kullback-Leibler divergence appearing in a pseudo likelihood of an MMM. Furthermore, a q-multinomial distribution was formulated, which acts as the Tsallis statistical counter for multinomial distributions in standard statistics. The proposed algorithm is constructed by fuzzifying a q-multinomial mixture model, by means of regularizing q-divergence appearing in a pseudo likelihood of the model. The proposed algorithm not only reduces into the q-multinomial mixture model, but also reduces into conventional fuzzy co-clustering models with specified sets of parameter values. In numerical experiments, the properties of the membership of the proposed method are observed.
UR - http://www.scopus.com/inward/record.url?scp=85030147973&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85030147973&partnerID=8YFLogxK
U2 - 10.1109/FUZZ-IEEE.2017.8015398
DO - 10.1109/FUZZ-IEEE.2017.8015398
M3 - Conference contribution
AN - SCOPUS:85030147973
T3 - IEEE International Conference on Fuzzy Systems
BT - 2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017
Y2 - 9 July 2017 through 12 July 2017
ER -