Local Feature Weighting in Nearest Prototype Classification
نویسندگان
چکیده
منابع مشابه
Class Dependent Feature Weighting and K-Nearest Neighbor Classification
Feature weighting in supervised learning concerns the development of methods for quantifying the capability of features to discriminate instances from different classes. A popular method for this task, called RELIEF, generates a feature weight vector from a given training set, one weight for each feature. This is achieved by maximizing in a greedy way the sample margin defined on the nearest ne...
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Nearest-neighbor algorithms are known to depend heavily on their distance metric. In this paper, we investigate the use of a weighted Euclidean metric in which the weight for each feature comes from a small set of options. We describe Diet, an algorithm that directs search through a space of discrete weights using cross-validation error as its evaluation function. Although a large set of possib...
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ژورنال
عنوان ژورنال: IEEE Transactions on Neural Networks
سال: 2008
ISSN: 1045-9227,1941-0093
DOI: 10.1109/tnn.2007.902955