Aha, D. and Kibler, D. (1989) Noise-tolerant instace-based learning algorithms. Home/Search Document Not in Database Summary Related Articles |
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A Weighted Nearest Neighbor Algorithm for Learning with.. - Cost, Salzberg (1993) (166 citations) (Correct)
....of sufficient data for learning. For example, instance based learning programs (also called exemplar based (Salzberg, 1990) or nearest neighbor (Cover and Hart, 1967) methods) which learn by storing examples as points in a feature space, require some means of measuring distance between examples (Aha, 1989; Aha and Kibler, 1989; Salzberg, 1989; Cost and Salzberg, 1990) An example is usually a vector of feature values plus a category label. When the features are numeric, normalized Euclidean distance can be used to compare examples. However, when the feature values have symbolic, unordered values ....
....data for learning. For example, instance based learning programs (also called exemplar based (Salzberg, 1990) or nearest neighbor (Cover and Hart, 1967) methods) which learn by storing examples as points in a feature space, require some means of measuring distance between examples (Aha, 1989; Aha and Kibler, 1989; Salzberg, 1989; Cost and Salzberg, 1990) An example is usually a vector of feature values plus a category label. When the features are numeric, normalized Euclidean distance can be used to compare examples. However, when the feature values have symbolic, unordered values (e.g. the letters of ....
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Aha, D. and Kibler, D. (1989) Noise-tolerant instace-based learning algorithms.
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