HAG
发表于 2025-3-21 19:35:55
书目名称Advances in Knowledge Discovery and Data Mining影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0148635<br><br> <br><br>书目名称Advances in Knowledge Discovery and Data Mining影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0148635<br><br> <br><br>书目名称Advances in Knowledge Discovery and Data Mining网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0148635<br><br> <br><br>书目名称Advances in Knowledge Discovery and Data Mining网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0148635<br><br> <br><br>书目名称Advances in Knowledge Discovery and Data Mining被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0148635<br><br> <br><br>书目名称Advances in Knowledge Discovery and Data Mining被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0148635<br><br> <br><br>书目名称Advances in Knowledge Discovery and Data Mining年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0148635<br><br> <br><br>书目名称Advances in Knowledge Discovery and Data Mining年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0148635<br><br> <br><br>书目名称Advances in Knowledge Discovery and Data Mining读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0148635<br><br> <br><br>书目名称Advances in Knowledge Discovery and Data Mining读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0148635<br><br> <br><br>
Apogee
发表于 2025-3-22 00:16:33
978-3-319-93033-6Springer International Publishing AG, part of Springer Nature 2018
arboretum
发表于 2025-3-22 01:44:39
Dean D. T. Maglinte,Hans Herlingerremely time consuming and expensive. In this paper we propose strategies for estimating performance of a classifier using as little labeling resource as possible. Specifically, we assume a labeling budget is given and the goal is to get a good estimate of the classifier performance using the provide
PAEAN
发表于 2025-3-22 06:39:05
Dean D. T. Maglinte,Hans Herlingerwith social data, such as the tweet stream generated by Twitter users in chronological order. A salient, and perhaps also the most interesting, feature of such user-generated content is its never-failing novelty, which, unfortunately, would challenge most traditional pre-trained classification model
macabre
发表于 2025-3-22 09:20:25
Dean D. T. Maglinte,Hans Herlinger implications, subsumptions or exclusions in a human-comprehensible and interpretable manner. However, the induction of rules with multiple labels in the head is particularly challenging, as the number of label combinations which must be taken into account for each rule grows exponentially with the
加剧
发表于 2025-3-22 14:16:08
Münster Studies of Coronary Heart Diseaseassifier quality are crucial aspects of multi-label classification. In this paper, we propose a multi-structure SVM (called MSSVM) which allows the user to hypothesize multiple label interaction structures and helps to identify their importance in improving generalization performance. We design an e
ERUPT
发表于 2025-3-22 18:47:24
Werner H. Hauss,Robert W. Wisslersemantic and syntactic features are well studied, global category information has been mostly ignored within the NN based framework. Samples with the same sentiment category should have similar vectors in represent space. Motivated by this, we propose a novel global sentiment centroids based neural
农学
发表于 2025-3-22 23:33:50
Fertilization and Embryo Culture,wever, it shows several limitations. First, random shapelet forest requires a large training cost for split threshold searching. Second, a single shapelet provides limited information for only one branch of the decision tree, resulting in insufficient accuracy and interpretability. Third, randomized
addict
发表于 2025-3-23 01:23:30
http://reply.papertrans.cn/15/1487/148635/148635_9.png
土坯
发表于 2025-3-23 06:34:37
Results from In Vitro Fertilization,eads to a classifier with a reject option, that allows the user to limit the number of erroneous predictions made on the test set, without any need to reveal the true labels of the test objects. The method described in this paper works by estimating the cumulative error count on a set of predictions