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