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WILF
2007
Springer
98views Fuzzy Logic» more  WILF 2007»
10 years 9 months ago
Possibilistic Clustering in Feature Space
In this paper we propose the Possibilistic C-Means in Feature Space and the One-Cluster Possibilistic C-Means in Feature Space algorithms which are kernel methods for clustering in...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
ISNN
2011
Springer
9 years 5 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
AAAI
2012
8 years 5 months ago
Discriminative Clustering via Generative Feature Mapping
Existing clustering methods can be roughly classified into two categories: generative and discriminative approaches. Generative clustering aims to explain the data and thus is ad...
Liwei Wang, Xiong Li, Zhuowen Tu, Jiaya Jia
CAIP
1995
Springer
189views Image Analysis» more  CAIP 1995»
10 years 6 months ago
Spatial and Feature Space Clustering: Applications in Image Analysis
We propose a novel approach to image segmentation, called feature and spatial domain clustering. The method is devised to group pixel data by taking into account simultaneously bo...
Jiri Matas, Josef Kittler
SDM
2008
SIAM
136views Data Mining» more  SDM 2008»
10 years 4 months ago
Exploration and Reduction of the Feature Space by Hierarchical Clustering
In this paper we propose and test the use of hierarchical clustering for feature selection. The clustering method is Ward's with a distance measure based on GoodmanKruskal ta...
Dino Ienco, Rosa Meo
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