An F-Measure for Evaluation of Unsupervised Clustering with Non-Determined Number of Clusters

TitleAn F-Measure for Evaluation of Unsupervised Clustering with Non-Determined Number of Clusters
Publication TypeUnpublished
Year of Publication2008
AuthorsMarxer, R., & Purwins H.
AbstractIn unsupervised learning, such as clustering, the problem occurs how to evaluate the results. In particular, neither the number of clusters nor the mapping between eventually known reference classes, e.g. generated from annotations, and the clusters are known. In this report, a method is suggested that adapts the F-measure for supervised classification to the unsupervised case.
preprint/postprint documenthttp://mtg.upf.edu/files/publications/unsuperf.pdf
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