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Titlebook: Advances in Artificial Intelligence - IBERAMIA 2002; 8th Ibero-American C Francisco J. Garijo,José C. Riquelme,Miguel Toro Conference proce

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樓主: encroach
51#
發(fā)表于 2025-3-30 11:56:30 | 只看該作者
J. M. Van Tuyl,K. B. Lim,M. S. Ramannadied and compared. The first one includes genetic algorithms (GA) and the second is based on principal component analysis (PCA). These methods are conceptually very different. While GA interacts with the neural network in the selection process, PCA only depends on the values of the initial set of features.
52#
發(fā)表于 2025-3-30 13:47:48 | 只看該作者
53#
發(fā)表于 2025-3-30 16:54:25 | 只看該作者
Chemical Composition of Zigzag Clover (, L.)d as a smaller effect on the quality of recommendations. Finally, we present situations that illustrate the advantage of providing recommendation as a ranking of the candidate algorithms, rather than as the single algorithm which is expected to perform best.
54#
發(fā)表于 2025-3-30 22:09:23 | 只看該作者
Insect Biotypes and Host Plant Resistance,rent stage of the reasoning cycle of the case-based reasoning system to retrieve, to adapt and to review the proposed solution to the problem. This system has been used to predict the red tides that appear in the coastal waters of the north west of the Iberian Peninsula. The results obtained from those experiments are presented.
55#
發(fā)表于 2025-3-31 02:27:35 | 只看該作者
56#
發(fā)表于 2025-3-31 05:14:34 | 只看該作者
57#
發(fā)表于 2025-3-31 11:41:17 | 只看該作者
O. Akinroluyo,G. Statkevi?iūt?,V. Keme?yt?oach similar to that of Query By Committee within the active learning setting. The method was applied to the real-world astronomical task of automated prediction of stellar atmospheric parameters, as well as to some benchmark learning problems showing a considerable improvement in classification accuracy over conventional algorithms.
58#
發(fā)表于 2025-3-31 16:46:37 | 只看該作者
59#
發(fā)表于 2025-3-31 17:55:45 | 只看該作者
60#
發(fā)表于 2025-4-1 00:39:02 | 只看該作者
Asymmetric Neighbourhood Selection and Support Aggregation for Effective Classification978-0-230-00072-8
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