TY - GEN
T1 - Clustering with the fisher score
AU - Tsuda, Koji
AU - Kawanabe, Motoaki
AU - Müller, Klaus Robert
PY - 2003
Y1 - 2003
N2 - Recently the Fisher score (or the Fisher kernel) is increasingly used as a feature extractor for classification problems. The Fisher score is a vector of parameter derivatives of loglikelihood of a probabilistic model. This paper gives a theoretical analysis about how class information is preserved in the space of the Fisher score, which turns out that the Fisher score consists of a few important dimensions with class information and many nuisance dimensions. When we perform clustering with the Fisher score, K-Means type methods are obviously inappropriate because they make use of all dimensions. So we will develop a novel but simple clustering algorithm specialized for the Fisher score, which can exploit important dimensions. This algorithm is successfully tested in experiments with artificial data and real data (amino acid sequences).
AB - Recently the Fisher score (or the Fisher kernel) is increasingly used as a feature extractor for classification problems. The Fisher score is a vector of parameter derivatives of loglikelihood of a probabilistic model. This paper gives a theoretical analysis about how class information is preserved in the space of the Fisher score, which turns out that the Fisher score consists of a few important dimensions with class information and many nuisance dimensions. When we perform clustering with the Fisher score, K-Means type methods are obviously inappropriate because they make use of all dimensions. So we will develop a novel but simple clustering algorithm specialized for the Fisher score, which can exploit important dimensions. This algorithm is successfully tested in experiments with artificial data and real data (amino acid sequences).
UR - http://www.scopus.com/inward/record.url?scp=84898958024&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84898958024
SN - 0262025507
SN - 9780262025508
T3 - Advances in Neural Information Processing Systems
BT - Advances in Neural Information Processing Systems 15 - Proceedings of the 2002 Conference, NIPS 2002
PB - Neural information processing systems foundation
T2 - 16th Annual Neural Information Processing Systems Conference, NIPS 2002
Y2 - 9 December 2002 through 14 December 2002
ER -