- 相关规则, 相关法则
- non-crossing correlation rule: 不交叉对比原则
- orbital correlation rule: 轨道相关法则
- orbital-correlation rule: 轨域关联法则
- correlation: n. 相互关系，相关(性)；对比；交互作用；【数学】对射，异射。 correlation index 关联指数。 correlation mineral 对比矿物。
- no correlation: 无相关
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correlation rule中文什么意思
- 相关规则, 相关法则
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例句与用法
- this method includes two kinds of observation data for the correlation rule, hence resulting in enhanced spatial resolving capability . weighted track fusion with cep as weight is proposed . this method has less calculation and notable result
同时根据无源定位系统观测误差的分布特性,提出了以为权因子的加权航迹融合算法,该融合算法计算量小,效果显著。 - then statistic correlation concept was introduced and based on which the rule interestingness measure was defined what we are interested in during the mining is those rules with strong item correlation . so the interesting measure introduced in this paper severed as a constraint for those independent or negative correlation rules . with it associated with the support and the confidence we can find only interesting or useful rules from data sets
而我们的目的就是找出有益于决策的用户感兴趣的规则，所以对于关联规则挖掘中许多规则是无趣甚至是误导的情况，文中首先对其作了分析，针对项目集中可能出现的项目间的独立和负相关情况，文中引入了概率论的统计相关概念，并在它的基础上定义了有趣度量ri，把有趣度结合到支持?信任框架的关联规则挖掘中。 - abstract : in this paper, a fuzzy track correlation algorithm in clutter was studied . the computation and evaluation methods of the fuzzy measure of track correlation between two tracks are discussed, the fuzzy track correlation rule is described as well . moreover, the algorithm is simulated . the simulation results show that the performance of fuzzy track correlation algorithm has obvious improvement for data associate
文摘:运用现代数学中的综合分析方法，对杂波环境下多传感器多目标跟踪中的模糊数据关联算法进行了研究，讨论了两航迹状态估计向量间关联度的度量、评价方法和模糊关联准则，并对算法进行了仿真分析，结果证明模糊关联算法对数据关联的质量有明显改善。 - outlier detection is a very important technique in data mining . in this paper, a more practicable system on outlier mining technique in high-dimensional is presented, which uses reduction character of rough set to cut out some inessential attributes and then mines outliers in subspace of every correlation rules
本文提出了对高维空间下离群点挖掘技术上的一个改进，即利用粗糙集的约简特性对高维空间下的数据属性进行约简，通过约简一些无关紧要的属性来减少高维空间的维数。