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A non-parametric method for supervised pattern recognition is presented. The method is of the classmodelling type, meaning that a classification rule is developed for each class, using the dissimilaritiesbetween the objects of the class. The dissimilarities between the objects within a class are related to thedistances between all pairs of training objects. As distance metric, a measure is proposed that takes thecorrelation between the interval-scale variables into account, and that moreover can be used for mixedtypes of variables. The classification rule is based on the construction of a boundary in the measurementspace. For the determination of the class boundary, several strategies are proposed and compared. The performance of the technique is evaluated on the basis of several data sets. Comparison with theclass modelling technique UNEQ shows its usefulness for practical applications. 相似文献
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ZHAO Junfeng LIU Chiyang WANG Xiaomei ZHANG Can Chemistry Postdoctoral Program of Northwest University Xi'an Shaanxi China State Key Laboratory of Continental Dynamics Northwest University China 《《地质学报》英文版》2009,83(2)
Based on the integrated study of structure attributions and characteristics of the original basin in combination with lithology and lithofacies,sedimentary provenance analysis and thickness distribution of the Mesozoic Ordos Basin,it is demonstrated that the depocenters migrated counterclockwise from southeast to the north and then to the southwest from the Middle-Late Triassic to the Early Cretaceous.There were no unified and larger-scale accumulation centers except several small isolated accumulation c... 相似文献