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Titlebook: Advances on Smart and Soft Computing; Proceedings of ICAC Faisal Saeed,Tawfik Al-Hadhrami,Errais Mohammed Conference proceedings 2021 The

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21#
發(fā)表于 2025-3-25 06:13:24 | 只看該作者
Context and Connection in Metaphorthey are employed in identifying dementia from clinical datasets. It has been found that support vector machine and random forest perform better on datasets coming from open access repositories such as open access series of imaging studies, Alzheimer’s disease neuroimaging initiative and dementia bank datasets.
22#
發(fā)表于 2025-3-25 09:51:23 | 只看該作者
23#
發(fā)表于 2025-3-25 15:09:27 | 只看該作者
24#
發(fā)表于 2025-3-25 18:31:44 | 只看該作者
SMOTE–ENN-Based Data Sampling and Improved Dynamic Ensemble Selection for Imbalanced Medical Data Clmbalanced medical datasets. The suggested approach is based on the combination of an improved dynamic ensemble selection called META-DES framework combined with a hybrid sampling method called SMOTE–ENN. The experimental results prove the superiority of the proposed ensemble learning system using three UCI datasets.
25#
發(fā)表于 2025-3-25 23:09:44 | 只看該作者
Performance Comparison of Machine Learning Techniques in Identifying Dementia from Open Access Clinithey are employed in identifying dementia from clinical datasets. It has been found that support vector machine and random forest perform better on datasets coming from open access repositories such as open access series of imaging studies, Alzheimer’s disease neuroimaging initiative and dementia bank datasets.
26#
發(fā)表于 2025-3-26 03:11:53 | 只看該作者
27#
發(fā)表于 2025-3-26 04:43:23 | 只看該作者
28#
發(fā)表于 2025-3-26 09:58:06 | 只看該作者
29#
發(fā)表于 2025-3-26 13:54:33 | 只看該作者
A Deep Learning Architecture for Profile Enrichment and Content Recommendationa in order to enrich the profile of the user. Then based on the history of user ratings as well as data on users and items (useful information such as genre, year, tag and rating), we develop a framework for deep learning to learn a similarity function between users and predict item ratings. We eval
30#
發(fā)表于 2025-3-26 17:08:51 | 只看該作者
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