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IJCNN
2008
IEEE
14 years 1 months ago
Ranking and selecting clustering algorithms using a meta-learning approach
Abstract— We present a novel framework that applies a metalearning approach to clustering algorithms. Given a dataset, our meta-learning approach provides a ranking for the candi...
Marcílio Carlos Pereira de Souto, Ricardo B...
CEC
2005
IEEE
14 years 1 months ago
Multiobjective clustering around medoids
Abstract- The large majority of existing clustering algorithms are centered around the notion of a feature, that is, individual data items are represented by their intrinsic proper...
Julia Handl, Joshua D. Knowles
JMLR
2012
11 years 10 months ago
Maximum Margin Temporal Clustering
Temporal Clustering (TC) refers to the factorization of multiple time series into a set of non-overlapping segments that belong to k temporal clusters. Existing methods based on e...
Minh Hoai Nguyen, Fernando De la Torre
SSPR
2004
Springer
14 years 24 days ago
Clustering Variable Length Sequences by Eigenvector Decomposition Using HMM
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
Fatih Murat Porikli
IWINAC
2009
Springer
14 years 1 days ago
Results of an Adaboost Approach on Alzheimer's Disease Detection on MRI
Abstract. In this paper we explore the use of the Voxel-based Morphometry (VBM) detection clusters to guide the feature extraction processes for the detection of Alzheimer's d...
Alexandre Savio, Maite García-Sebasti&aacut...