Z. Bodó, Z. Minier & L. Csató; JMLR W&CP
Active Learning with Clustering
Active learning is an important ﬁeld of machine learning and it is becoming more
widely used in case of problems where labeling the examples in the training data set is expensive.
In this paper we present a clustering-based algorithm used in the Active Learning Challenge
). The algorithm is based on
graph clustering with normalized cuts, and uses k
-means to extract representative
points from the data and approximate spectral clustering for eﬃciently performing the
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