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发表于 2025-3-21 16:06:21
书目名称Innovations in Classification, Data Science, and Information Systems影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0467053<br><br> <br><br>书目名称Innovations in Classification, Data Science, and Information Systems影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0467053<br><br> <br><br>书目名称Innovations in Classification, Data Science, and Information Systems网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0467053<br><br> <br><br>书目名称Innovations in Classification, Data Science, and Information Systems网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0467053<br><br> <br><br>书目名称Innovations in Classification, Data Science, and Information Systems被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0467053<br><br> <br><br>书目名称Innovations in Classification, Data Science, and Information Systems被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0467053<br><br> <br><br>书目名称Innovations in Classification, Data Science, and Information Systems年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0467053<br><br> <br><br>书目名称Innovations in Classification, Data Science, and Information Systems年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0467053<br><br> <br><br>书目名称Innovations in Classification, Data Science, and Information Systems读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0467053<br><br> <br><br>书目名称Innovations in Classification, Data Science, and Information Systems读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0467053<br><br> <br><br>
Encumber
发表于 2025-3-21 20:36:30
Innovations in Classification, Data Science, and Information Systems978-3-540-26981-6Series ISSN 1431-8814 Series E-ISSN 2198-3321
让空气进入
发表于 2025-3-22 03:35:51
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Engaged
发表于 2025-3-22 07:10:12
Studies in Classification, Data Analysis, and Knowledge Organizationhttp://image.papertrans.cn/i/image/467053.jpg
潜伏期
发表于 2025-3-22 10:32:05
https://doi.org/10.1007/b138406Analysis; Time series; clustering; controlling; data analysis; information system; learning; production; sta
FIN
发表于 2025-3-22 15:52:50
Regression Clustering with Redescending M-Estimatorsusters. We work out the method not only for classical regression but also for orthogonal regression and multivariate locations and give consistency results for all three cases. The approach of orthogonal regression is applied to the identification of edges in noisy images.
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发表于 2025-3-22 17:14:20
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发表于 2025-3-23 00:23:44
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脆弱带来
发表于 2025-3-23 03:57:37
Symbolic Classifier with Convex Hull Based Dissimilarity Function (or a set of regions) in ℜ. defined by the convex hull of the objects belonging to this class. In the allocation step, the assignment of a new object to a class is based on a dissimilarity matching function that compares the class description (a region or a set of regions) with a point in ℜ.. This
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发表于 2025-3-23 05:34:29
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