凹槽
发表于 2025-3-23 11:59:22
Degrees of models with prescribed Scott set, define a distance between pairs of values of the same categorical attribute, since they are not ordered. In this paper, we propose a method to learn a context-based distance for categorical attributes. The key intuition of this work is that the distance between two values of a categorical attribute
冰雹
发表于 2025-3-23 16:02:13
Julia F. Knight,Alistair H. Lachlanare readily available while only a small number of labeled training samples are accessible. The paper proposes a semi-supervised classifier that integrates a clustering based Expectation Maximization (EM) algorithm into radial basis function (RBF) neural networks and can learn for classification fro
landfill
发表于 2025-3-23 18:37:26
https://doi.org/10.1007/BFb0082228. However, .-NN relies usually on the use of Euclidean distances that fail often to reflect accurately the sample proximities. Non Euclidean dissimilarities focus on different features of the data and should be integrated in order to reduce the misclassification errors..In this paper, we learn a lin
probate
发表于 2025-3-24 01:32:39
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Infraction
发表于 2025-3-24 03:07:12
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Bravura
发表于 2025-3-24 10:15:24
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Galactogogue
发表于 2025-3-24 14:37:46
Classification Theory of Riemann Surfaces In this paper, we tackle sequential data and we define an exact condensed representation for sequential patterns according to the frequency-based measures. These measures are often used, typically in order to evaluate classification rules. Furthermore, we show how to infer the best patterns accordi
雪白
发表于 2025-3-24 17:09:42
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耐寒
发表于 2025-3-24 20:27:51
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Decongestant
发表于 2025-3-25 00:44:12
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