习惯
发表于 2025-3-21 16:10:38
书目名称Discovery Science影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0281056<br><br> <br><br>书目名称Discovery Science影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0281056<br><br> <br><br>书目名称Discovery Science网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0281056<br><br> <br><br>书目名称Discovery Science网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0281056<br><br> <br><br>书目名称Discovery Science被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0281056<br><br> <br><br>书目名称Discovery Science被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0281056<br><br> <br><br>书目名称Discovery Science年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0281056<br><br> <br><br>书目名称Discovery Science年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0281056<br><br> <br><br>书目名称Discovery Science读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0281056<br><br> <br><br>书目名称Discovery Science读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0281056<br><br> <br><br>
ALERT
发表于 2025-3-21 21:59:12
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Cpr951
发表于 2025-3-22 01:29:58
CF4CF-META: Hybrid Collaborative Filtering Algorithm Selection Frameworkis paper starts with the hypothesis that the integration of both approaches in a unified algorithm selection framework can improve the predictive performance. Hence, this work introduces CF4CF-META, an hybrid framework which leverages both data and algorithm ratings within a modified Label Ranking m
Epithelium
发表于 2025-3-22 05:12:44
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同位素
发表于 2025-3-22 12:46:36
Selection of Relevant and Non-Redundant Multivariate Ordinal Patterns for Time Series Classificationture .traction (.), simultaneously extracts and scores the relevance and redundancy of ordinal patterns without training a classifier. As a filter-based approach, . aims to select a set of relevant patterns with complementary information. Hence, using our scoring function based on the principles of
Brain-Imaging
发表于 2025-3-22 15:13:17
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Brain-Imaging
发表于 2025-3-22 18:51:17
0302-9743 arning; reinforcement learning; streams and time series; subgroup and subgraph discovery; text mining; and applications..978-3-030-01770-5978-3-030-01771-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
frozen-shoulder
发表于 2025-3-23 00:25:34
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neologism
发表于 2025-3-23 02:45:10
https://doi.org/10.1007/978-1-4612-5517-8 closest majority samples to remove LS-SVM’s bias due to data imbalance. Two variations of BBMO are studied: BBMO1 for the linearly separable case which uses the Lagrange multipliers to extract boundary samples from both classes, and the generalized BBMO2 for the non-linear case which uses the kerne
线
发表于 2025-3-23 05:48:42
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