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Titlebook: Advances in Computational Intelligence; 13th International W Ignacio Rojas,Gonzalo Joya,Andreu Catala Conference proceedings 2015 Springer

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41#
發(fā)表于 2025-3-28 17:41:43 | 只看該作者
,Konzeption des Konstrukts ?Businessplan“,ession Trees (CART) and Naive Bayes (NB) to identify non spontaneous saccades in clinical electrooculography tests. Our approach tries to solve problems like the use of manually established thresholds present in classical methods like identification by velocity threshold (I-VT) or identification by
42#
發(fā)表于 2025-3-28 21:31:15 | 只看該作者
43#
發(fā)表于 2025-3-28 23:54:49 | 只看該作者
https://doi.org/10.1007/978-3-8350-9495-6 network models for ordinal regression. The process for obtaining the coefficients is carried out in several steps. In the first step we use an evolutionary algorithm to determine the structure of the RBF neural network model, in a second step we transform the initial feature space (covariate space)
44#
發(fā)表于 2025-3-29 04:13:11 | 只看該作者
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發(fā)表于 2025-3-29 07:35:08 | 只看該作者
46#
發(fā)表于 2025-3-29 11:26:10 | 只看該作者
47#
發(fā)表于 2025-3-29 15:47:34 | 只看該作者
,Konzeption des Konstrukts ?Businessplan“,near equation system instead of solving a quadratic programming optimization problem. Nevertheless, the absence of sparseness in the solution (i.e. the Lagrange multipliers vector) obtained is a significant drawback which must be overcome. This work presents a new approach to building Sparse Least S
48#
發(fā)表于 2025-3-29 20:58:15 | 只看該作者
,Konzeption des Konstrukts ?Businessplan“,his paper evaluates ensemble learning methods using the Minimal Learning Machines (MLM), a recently proposed supervised learning algorithm. Additionally, we introduce an alternative output estimation procedure to reduce the complexity of the standard MLM. The proposed methods are evaluated on real d
49#
發(fā)表于 2025-3-30 00:51:16 | 只看該作者
50#
發(fā)表于 2025-3-30 06:13:45 | 只看該作者
Women in International Management,redict the market’s behaviour can modify the market itself so it is more predictable. In this context, the key element is to find out which variables are used to build the model in a macroeconomic environment. This paper presents an application of kernel methods to predict the EUR/USD relationship p
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