DNR215
发表于 2025-3-26 22:39:25
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lethargy
发表于 2025-3-27 01:12:55
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Receive
发表于 2025-3-27 06:47:31
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符合你规定
发表于 2025-3-27 12:49:04
Shoshana Marcus,Dina Sokol,Sarah Zelikovitzd, the fractional form of Jacobi polynomials will be introduced, and the validation according to Mercer conditions will be proved. Finally, a comparison of the obtained results over a well-known dataset will be provided, using the mentioned kernels with some other orthogonal kernels as well as RBF a
不透明
发表于 2025-3-27 15:30:34
Edgar Chavez,Eric S. Tellezffusion, and wave. We used the modal Legendre functions, which have been introduced in Chap. . and have been applied several times in the previous chapters as the least squares support vector regression algorithm’s kernel basis in the presented method. The uniqueness of the obtained solution is prov
Communal
发表于 2025-3-27 18:52:13
Jaroslav Hlaváč,Martin Kopp,Jan Kohout,Tomá Skopalffusion, and wave. We used the modal Legendre functions, which have been introduced in Chap. . and have been applied several times in the previous chapters as the least squares support vector regression algorithm’s kernel basis in the presented method. The uniqueness of the obtained solution is prov
dissent
发表于 2025-3-28 00:28:40
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领导权
发表于 2025-3-28 04:20:33
Omar Shahbaz Khan,Martin Aumüller,Björn Þór Jónssond big data applications of support vector algorithms are growing. Consequently, the Compute Unified Device Architecture (CUDA) parallelizing the procedure of support vector algorithms based on orthogonal kernel functions is presented. The book sheds light on how to use support vector algorithms base
我悲伤
发表于 2025-3-28 09:27:33
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Demonstrate
发表于 2025-3-28 14:25:46
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