mandatory
发表于 2025-3-21 17:34:18
书目名称Granular Computing in Decision Approximation影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0387858<br><br> <br><br>书目名称Granular Computing in Decision Approximation影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0387858<br><br> <br><br>书目名称Granular Computing in Decision Approximation网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0387858<br><br> <br><br>书目名称Granular Computing in Decision Approximation网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0387858<br><br> <br><br>书目名称Granular Computing in Decision Approximation被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0387858<br><br> <br><br>书目名称Granular Computing in Decision Approximation被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0387858<br><br> <br><br>书目名称Granular Computing in Decision Approximation年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0387858<br><br> <br><br>书目名称Granular Computing in Decision Approximation年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0387858<br><br> <br><br>书目名称Granular Computing in Decision Approximation读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0387858<br><br> <br><br>书目名称Granular Computing in Decision Approximation读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0387858<br><br> <br><br>
byline
发表于 2025-3-21 21:05:16
Marc-Thorsten Hütt,Manuel Dehnertrategy, see Sect. ., on the accuracy of the respective classifier. As observed in Chaps. . and ., we are at liberty in selecting the strategy . which defines the method of choice of a covering of the universe of the data set with granules.
MIR
发表于 2025-3-22 03:24:55
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一窝小鸟
发表于 2025-3-22 07:14:04
Covering Strategies,rategy, see Sect. ., on the accuracy of the respective classifier. As observed in Chaps. . and ., we are at liberty in selecting the strategy . which defines the method of choice of a covering of the universe of the data set with granules.
可商量
发表于 2025-3-22 09:49:54
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搏斗
发表于 2025-3-22 13:31:01
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搏斗
发表于 2025-3-22 19:58:53
Petrinetze als Beschreibungsmittel,In this chapter, we recall basic facts about data classifiers in machine learning. Our survey is focused on Bayes and kNN classifiers which are employed in our experiments. Some basic facts form Computational Learning Theory are followed by an account of classifiers in real decision systems, mostly elaborated within Rough Set Theory.
词汇记忆方法
发表于 2025-3-22 21:36:14
Lebensereignisse: Übergänge im LebenslaufIn this chapter, we intend to introduce the reader into the realm of granular reflections induced from decision systems by means of similarity relations being rough inclusions or their weaker variants.
国家明智
发表于 2025-3-23 02:17:03
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树木中
发表于 2025-3-23 08:38:28
Methoden der Fehler- und AusgleichsrechnungIn this chapter, we study the performance of Bayes classifier on granular structures. From results in Table ., we infer that Bayes classifier is well suited for granular cases as for most tested data its accuracy in best cases is better in granulated cases then in non-granulated ones.