Abstract

. It is widely reported in the literature that incremental clustering systems suffer from instance ordering effects and that under some orderings, extremely poor clusterings may be obtained. In this paper we present a new general strategy aimed to mitigate these effects, the Not-Yet strategy which has a general and open formulation and it is not coupled to any particular system. Unlike other proposals, this strategy maintains the incremental nature of learning process. In addition, we propose a classification of strategies to avoid ordering effects which clarifies the benefits and disadvantages we can expect from the proposal made in the paper as well from existing ones. A particular implementation of the Not-Yet strategy is used to conduct several experiments. Results suggest that the strategy improves the clustering quality. We also show that, when combined with other local strategies, the Not-Yet strategy allows the clustering system to get high quality clusterings. Keywords: Machin...

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