卷发
发表于 2025-3-23 11:29:38
Eric Linhart,Friedrich Hedtrichcomputational cost. This paper describes a novel method to overcome this problem. A set of normalization values associated to the most frequent .-gramsis pre-computed and the model is smoothed with lower .-gramconnectionist or statistical models. The proposed approach is favourably compared to stand
种属关系
发表于 2025-3-23 16:46:15
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GEM
发表于 2025-3-23 19:33:48
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Lice692
发表于 2025-3-24 00:42:40
https://doi.org/10.1007/978-3-658-16714-1asses. Solving a classification task using such an imbalanced data-set is difficult due to the bias of the training towards the majority classes. The aim of this contribution is to analyse the performance of CO.RBFN, a cooperative-competitive evolutionary model for the design of RBFNs applied to cla
glans-penis
发表于 2025-3-24 03:38:06
‘Divide the Dollar’ Using Voting by Vetotead of selecting a subset of variables with forward or backward feature selection procedures, we modify the loss function in such a way that the maximal variation for each covariate is minimized, resulting in models which have sparse dependence on the features. Experiments on artificial data illust
外露
发表于 2025-3-24 06:35:12
Heinz Brestel,Adolf Freiherr von Kniggeet the index pair giving the maximum KKT violation and combines it with the updating heuristics of Smola and Schölkopf enforcing at each training iteration a . condition. In this work we shall present an alternative, much simpler procedure that selects the updating indices as those giving a maximum
CALL
发表于 2025-3-24 11:29:49
Jahrbuch für Kapitalanleger 1999 consider a Radial Basis Function Network and a Multi-Layer Perceptron. We examine the metrics of data complexity known as . over a wide range of data sets built from real data, and try to extract behaviour patterns from the results. We obtain rules that describe both good or bad behaviours of the A
群岛
发表于 2025-3-24 18:14:34
Thomas Schwinger,Hans Jörg Burmeister proposed technique is most effective when the reliability of the model significantly varies in different areas of input space, as it often happens in many real-world problems, allowing the user to predict how reliable is a given model for each specific situation. Alternatively, the proposed techniq
出生
发表于 2025-3-24 21:30:35
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LITHE
发表于 2025-3-25 01:40:29
Doris Immich,Christian Gremmelsand the sample covariance matrix around every input vector. This choice yields poor robustness for real input datasets. We propose to use the L1-median to estimate the local mean and covariance matrix with a low sensitivity to outliers. In addition to this, a smoothing phase is considered, which imp