Fuzzy Sets and Systems - Special issue: Preference modelling and applications
Soft Aggregation Methods in Case Based Reasoning
Applied Intelligence
Dealing with missing data: algorithms based on fuzzy set and rough set theories
Transactions on Rough Sets IV
Fuzzy nearest neighbor algorithms: Taxonomy, experimental analysis and prospects
Information Sciences: an International Journal
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The basic principle used in the construction of nearest-neighbor models is discussed. The induced ordered weighted averaging (IOWA) operators are shown to provide a useful formal structure for building nearest-neighbor models. A methodology for learning IOWA operator nearest-neighbor models is described. Various types of nearest-neighbor rules are investigated, including those based on a linguistic specification. The situation in which the value of interest lies in an ordinal set is also considered. It is shown that the weighted median provides a useful tool for constructing nearest-neighbor rules in this case