热情美女
发表于 2025-3-21 19:03:24
书目名称Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Metho影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0263975<br><br> <br><br>书目名称Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Metho影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0263975<br><br> <br><br>书目名称Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Metho网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0263975<br><br> <br><br>书目名称Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Metho网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0263975<br><br> <br><br>书目名称Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Metho被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0263975<br><br> <br><br>书目名称Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Metho被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0263975<br><br> <br><br>书目名称Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Metho年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0263975<br><br> <br><br>书目名称Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Metho年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0263975<br><br> <br><br>书目名称Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Metho读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0263975<br><br> <br><br>书目名称Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Metho读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0263975<br><br> <br><br>
男生如果明白
发表于 2025-3-21 21:16:09
http://reply.papertrans.cn/27/2640/263975/263975_2.png
grotto
发表于 2025-3-22 00:30:16
Udoka Okonta,Amin Hosseinian-Farphenomenon is addressed by the introduction of semi-supervised classification, in which a prediction model is derived from a training set consisting of both labelled and unlabelled data. Information in both the labelled and unlabelled parts of the training set can be used in the classification process.
拾落穗
发表于 2025-3-22 06:48:05
http://reply.papertrans.cn/27/2640/263975/263975_4.png
沙发
发表于 2025-3-22 12:47:23
CSR, Sustainability, Ethics & Governancequence, the recognition of minority instances is hampered. Since minority classes are usually the ones of interest, custom techniques are required to deal with such data skewness. We study them in this chapter.
CHAR
发表于 2025-3-22 15:10:43
http://reply.papertrans.cn/27/2640/263975/263975_6.png
CHAR
发表于 2025-3-22 18:15:47
Matthew D. Wood,Daniel A. HunterGenerally put, this book is on fuzzy rough set based methods for machine learning. We develop classification algorithms based on fuzzy rough set theory for several types of data relevant to real-world applications.
陪审团每个人
发表于 2025-3-22 21:42:51
http://reply.papertrans.cn/27/2640/263975/263975_8.png
Dawdle
发表于 2025-3-23 03:45:09
Matthew D. Wood,Daniel A. HunterAs noted in Chap. 1, the traditional fuzzy rough set model is intrinsically sensitive to noise and outliers in the data. One generalization to deal with this issue in an intuitive way is the ordered weighted average (OWA) based fuzzy rough set model, that replaces the strict minimum and maximum operators by more elaborate OWA aggregations.
泥瓦匠
发表于 2025-3-23 09:27:59
http://reply.papertrans.cn/27/2640/263975/263975_10.png