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Titlebook: Discovery Science; 26th International C Albert Bifet,Ana Carolina Lorena,Pedro H. Abreu Conference proceedings 2023 The Editor(s) (if appli

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樓主: damped
31#
發(fā)表于 2025-3-27 00:56:27 | 只看該作者
https://doi.org/10.1007/978-3-031-45275-8computing methodologies; artificial intelligence; machine learning; natural language processing; search
32#
發(fā)表于 2025-3-27 01:08:27 | 只看該作者
33#
發(fā)表于 2025-3-27 07:54:41 | 只看該作者
Discovery Science978-3-031-45275-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
34#
發(fā)表于 2025-3-27 11:27:23 | 只看該作者
35#
發(fā)表于 2025-3-27 16:22:24 | 只看該作者
Exploring the?Intricacies of?Neural Network Optimizationually only affects training time, reducing it by up to 80% or increasing it by 200%. In contrast, the hidden layer size does not consistently affect the considered performance metrics. The optimizer can significantly affect the model’s overall performance while also varying the training time, with A
36#
發(fā)表于 2025-3-27 18:54:02 | 只看該作者
iSOUP-SymRF: Symbolic Feature Ranking with?Random Forests in?Online Multi-target Regressionods’ parameters: the size of the ensemble and the number of selected features. Furthermore, to show the utility of iSOUP-SymRF and its rankings we use them in conjunction with two state-of-the-art online multi-target regression methods, iSOUP-Tree and AMRules, and analyze the impact of adding featur
37#
發(fā)表于 2025-3-28 01:51:49 | 只看該作者
38#
發(fā)表于 2025-3-28 03:22:11 | 只看該作者
39#
發(fā)表于 2025-3-28 09:08:23 | 只看該作者
40#
發(fā)表于 2025-3-28 11:43:14 | 只看該作者
: A Graph Convolutional Network-Based Approach for?Review Spam Detection author of a review to the reviewed item. Features of users, products and reviews are associated with nodes and edges, respectively..Experiments performed on publicly available review datasets prove the effectiveness of the proposed approach compared with some state-of-the-art approaches.
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