Roosevelt
发表于 2025-3-21 17:03:18
书目名称New Frontiers in Applied Data Mining影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0665233<br><br> <br><br>书目名称New Frontiers in Applied Data Mining影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0665233<br><br> <br><br>书目名称New Frontiers in Applied Data Mining网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0665233<br><br> <br><br>书目名称New Frontiers in Applied Data Mining网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0665233<br><br> <br><br>书目名称New Frontiers in Applied Data Mining被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0665233<br><br> <br><br>书目名称New Frontiers in Applied Data Mining被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0665233<br><br> <br><br>书目名称New Frontiers in Applied Data Mining年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0665233<br><br> <br><br>书目名称New Frontiers in Applied Data Mining年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0665233<br><br> <br><br>书目名称New Frontiers in Applied Data Mining读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0665233<br><br> <br><br>书目名称New Frontiers in Applied Data Mining读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0665233<br><br> <br><br>
finale
发表于 2025-3-21 20:44:12
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OTHER
发表于 2025-3-22 03:35:54
Feature Selection for Brain-Computer Interfaces,proved accuracy when used with suitable classification algorithms. The top three feature selectors in terms of classification accuracy were correlation-based feature selection, information gain and 1R ranking, with correlation based feature selection choosing the smallest number of features.
FOR
发表于 2025-3-22 06:21:05
Missing Phrase Recovering by Combining Forward and Backward Phrase Translation Tables, applied to both tables. We assessed our method on different combining weights by counting the missing phrases and calculating the BLEU scores and NIST scores. Approximately 7% of missing phrases are recovered and 1.3% of BLEU score is increased.
Legend
发表于 2025-3-22 10:24:16
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发电机
发表于 2025-3-22 13:41:52
Adaptive Methods for Classification in Arbitrarily Imbalanced and Drifting Data Streams,w distance measure for detecting distributional drift and examine its utility in weighting ensemble base classifiers. We employ a sequential validation framework, which we believe is the most meaningful option in the context of streaming imbalanced data.
Negligible
发表于 2025-3-22 18:26:22
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Chivalrous
发表于 2025-3-23 01:15:42
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recession
发表于 2025-3-23 03:08:25
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懦夫
发表于 2025-3-23 06:37:00
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