Dario García-García, Raúl Santos-Rodríguez, E. Parrado-Hernández
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Classifier-based affinities for clustering sets of vectors
We focus on the task of clustering sets of vectors. This can be seen as a special case of sequence clustering when the dynamics are not taken into account. We propose to use the error probability of binary classifiers to obtain a measure of the affinity between two sets so that a standard similarity-based clustering algorithm can be applied.
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