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挖掘速度的英文

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"挖掘速度"怎么读用"挖掘速度"造句

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  • digging speed

例句与用法

  • We present a new approach to mine ooa rules using fp - growth algorithm . our experimental results show that the algorithm is more
    实验表明,本文提出的方法相比用apriori算法或用dfree算法进行ooa挖掘速度更快。
  • All present user access pattern mining tools have some shortcomings , such as slow mining speed , unsuitable anonymous users , complicated usage , inefficiency , low mobility , much mining limitation and so on
    现有的用户访问模式挖掘工具都存在一些缺点,如:挖掘速度慢、不适用匿名用户、使用复杂、效率低、灵活性差、挖掘局限性大等。
  • Taditional association rule mining methods lack of focus on the results , and the procedure is slow . those algorithms express the regularities with low level primitive data , and the mining association reules are difficult to understand
    传统的关联规则挖掘缺少挖掘的针对性,挖掘速度慢,挖掘结果难于理解,挖掘结果的数量巨大,需要进行大量的筛选以便抽取出有用规则。
  • And it can find the same visiting pattern of the different interests - oriented user groups to enhance the quality recommended , by means of adjusting the number of clusters , uapomr system solve the contradiction between mining speed and nicety effectively for recommending in real - time
    通过调整聚类的个数, uapomr系统有效地解决了挖掘速度和挖掘准确性之间的矛盾,以达到在线推荐的目的。
  • Experiments show that fpmine runs two times as fast as the most recently proposed algorithm fp - growth and saves half the memory ; moreover , our algorithm has a quite good time and space scalability with the number of transactions , and has an excellent performance in dense database mining as well ; spf has excellent time and space efficiency ; fpmine - spf algorithm has a far taster speed in association rules mining than the widely used apriori algorithm and has wonderful scalability . association rules mining always generates too many rules , which makes ii difficult to pick the valuable rules where from
    实验表明,在相同数据集上,与fp - growth算法相比,算法fpmine的挖掘速度提高了一倍以上,而所需的存储空间减少了一半;随着数据库规模的增大,算法fpmine具有很好的可伸缩性;对于稠密数据集,本文算法也具有良好的性能; spf算法具有极好的时空效率; fpmine - spf算法挖掘关联规则的速度远快于较长期以来广泛使用的apriori算法,并有相当好的可伸缩性。
  • By the way this paper chooses the more effective dm algorithms by deep study in quite a few known algorithms employed in association rules , frequent episodes rules and trend analysis . to speed up producing association rule , this paper also introduces the aadd algorithm which is a upgrade algorithm from apriori
    同时本文通过对关联规则、模式序列和趋势分析的多种算法的深入的分析和比较,结合网络攻击检测的需求,为检测dos攻击选择合适有效的算法;并为加快关联规则挖掘速度,提出apriori算法的改进算法? ? aadd算法。
用"挖掘速度"造句  
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