平凡人
发表于 2025-3-21 16:43:22
书目名称Compression Schemes for Mining Large Datasets影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0231990<br><br> <br><br>书目名称Compression Schemes for Mining Large Datasets影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK0231990<br><br> <br><br>书目名称Compression Schemes for Mining Large Datasets网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0231990<br><br> <br><br>书目名称Compression Schemes for Mining Large Datasets网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK0231990<br><br> <br><br>书目名称Compression Schemes for Mining Large Datasets被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0231990<br><br> <br><br>书目名称Compression Schemes for Mining Large Datasets被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0231990<br><br> <br><br>书目名称Compression Schemes for Mining Large Datasets年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0231990<br><br> <br><br>书目名称Compression Schemes for Mining Large Datasets年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0231990<br><br> <br><br>书目名称Compression Schemes for Mining Large Datasets读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0231990<br><br> <br><br>书目名称Compression Schemes for Mining Large Datasets读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0231990<br><br> <br><br>
纹章
发表于 2025-3-21 22:46:34
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Enzyme
发表于 2025-3-22 01:10:51
,1919–1923 “Independence or Death!”,vide a better classification accuracy than the original dataset. In this direction, we implement the proposed scheme on two large datasets, one with binary-valued features and the other with float-point-valued features. At the end of the chapter, we provide bibliographic notes and a list of referenc
荒唐
发表于 2025-3-22 06:10:46
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不怕任性
发表于 2025-3-22 09:15:17
Product Mix and Diversification,ow the divide-and-conquer approach of multiagent systems improves handling huge datasets. We propose four multiagent systems that can help generating abstraction with big data. We provide suggested reading and bibliographic notes. A list of references is provided in the end.
洁净
发表于 2025-3-22 15:58:04
2191-6586 e in generating abstraction; reviews optimal prototype selection using genetic algorithms; suggests possible ways of dealing with big data problems using multiagent systems.978-1-4471-7055-6978-1-4471-5607-9Series ISSN 2191-6586 Series E-ISSN 2191-6594
洁净
发表于 2025-3-22 18:20:05
Data Mining Paradigms,n intermediate representation. The discussion on classification includes topics such as incremental classification and classification based on intermediate abstraction. We further discuss frequent-itemset mining with two directions such as divide-and-conquer itemset mining and intermediate abstracti
FOVEA
发表于 2025-3-23 00:18:28
Dimensionality Reduction by Subsequence Pruning,earest neighbors. This results in lossy compression in two levels. Generating compressed testing data forms an interesting scheme too. We demonstrate significant reduction in data and its working on large handwritten digit data. We provide bibliographic notes and references at the end of the chapter
FLUSH
发表于 2025-3-23 02:14:38
Data Compaction Through Simultaneous Selection of Prototypes and Features,vide a better classification accuracy than the original dataset. In this direction, we implement the proposed scheme on two large datasets, one with binary-valued features and the other with float-point-valued features. At the end of the chapter, we provide bibliographic notes and a list of referenc
Ornament
发表于 2025-3-23 06:57:02
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