Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Kathrin Bujna"'
Publikováno v:
Advances in Data Analysis and Classification. 14:147-173
In this paper, we present a theoretical and an experimental comparison of EM and SEM algorithms for different mixture models. The SEM algorithm is a stochastic variant of the EM algorithm. The qualitative intuition behind the SEM algorithm is simple:
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3aa83f83f0332dbda05876ede1895b78
https://doi.org/10.1007/s11634-019-00366-7
https://doi.org/10.1007/s11634-019-00366-7
Publikováno v:
ICDM
One of the most popular fuzzy clustering techniques is the fuzzy K-means algorithm (also known as fuzzy-c-means or FCM algorithm). In contrast to the K-means and K-median problem, the underlying fuzzy K-means problem has not been studied from a theor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d9259751054371e8c968752ac1caacb
https://doi.org/10.1109/icdm.2016.0094
https://doi.org/10.1109/icdm.2016.0094
Autor:
Kathrin Bujna, Johannes Blömer
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783319317496
We present new initialization methods for the expectation-maximization algorithm for multivariate Gaussian mixture models. Our methods are adaptions of the well-known $K$-means++ initialization and the Gonzalez algorithm. Thereby we aim to close the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50bea51e558d2480f21a1bb827685423
https://doi.org/10.1007/978-3-319-31750-2_24
https://doi.org/10.1007/978-3-319-31750-2_24
Publikováno v:
ICPR
In this paper we provide a new analysis of the SEM algorithm. Unlike previous work, we focus on the analysis of a single run of the algorithm. First, we discuss the algorithm for general mixture distributions. Second, we consider Gaussian mixture mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2757fd95c39e1348f4442511eb285ac0
https://doi.org/10.1109/icpr.2014.253
https://doi.org/10.1109/icpr.2014.253