rating n. 1.分等级;定等级;估价;估计;分摊,分配;【电学】测定,计算;〔美国〕(考试的)批分数。 2.额定值,定额;参量;工作能力;(商店的)信用程度;〔英国〕地方税征收额。 3.【航海】(船舰或海员的)等级;(汽车等的)规格;〔pl.〕〔英国〕刚入伍的船员。 4.(电台、电视台经调查确定的)节目受欢迎的程度。 a nominal rating 标准规格。 a power rating 额定功率。 n. 叱责,斥责。 give a sound rating 严厉申斥一顿。
classification n. 1.选别;分等,分级;分选。 2.【动、植】分类(法)。 〔分类级别为: phylum 【动物;动物学】及 division 【植物;植物学】门,class 纲,order 目,family 科,genus 属,species 种,variety 品种〕。 3.类别;等级;(文件的)保密级。 a classification yard (车站的)调车场。
The results of experiment show that the method is effective and the classification rate is higher 实验证明了该方法的有效性,而且分类效果很好。
From the result of experiments , we discover that different orders bring different classification rate of each sort 在试验中发现,输出单元对应的缺陷类别的不同顺序,系统的整体识别率的变化不大。
One - way analysis , minimum bias procedures and multiple regressions have been widely used in non - life classification rating 摘要对非寿险产品分类费率的厘定通常采用单项分析法、最小偏差法和多元线性回归等方法。
And discuss the means to resolve the problem . experiments with samples of surface detects show that classification rate is up to 90 % 通过实验证明本文的缺陷分类方法可以有效地识别本文所研究的冷轧带钢表面缺陷类型,识别率达到90 %以上。
By using the optimized covariance matrices to optimize the new regularized discriminant analysis ( rda ) , the correct classification rate is higher than that by the old rda 利用优化的协方差矩阵对正则化判别分析方法进行优化,其模式分类正确率有显著提高。
3 . classification and management of samples are discussed . a sort of defects is divided into several sorts , and the order of defects is adjusted to improve the classification rate 3 .针对本系统的实际情况,研究样本库的合理分类和管理,通过将某一大类分成合理的小类,会提高整体的识别率。
The simulation and application results show that the performance of the proposed method has so many advantages such as simple structure , quick convergence and high aggregate classification rate , that it can be applied in on - line detection and analysis of control chart 仿真结果和实际应用表明:该方法结构简单、收敛速度快,识别准确率高,能够满足控制图在线检测和分析的需要。
The latter classification method combined variable precision rough set model with k - nn classification method , so we can control the classification accuracy rate by the most endurable given error classification rate , then we can make the classification result conform to what we expect , and also some examples are given 后一种分类方法是将可变精度粗集模型与k - nn分类结合起来,从而可通过给定最大容忍的错误分类率来控制分类的准确度,使分类结果达到所期望的目的。并且给出了一些例子。
Network forensics is an important extension to present security infrastructure , and is becoming the research focus of forensic investigators and network security researchers . however many challenges still exist in conducting network forensics : the sheer amount of data generated by the network ; the comprehensibility of evidences extracted from collected data ; the efficiency of evidence analysis methods , etc . against above challenges , by taking the advantage of both the great learning capability and the comprehensibility of the analyzed results of decision tree technology and fuzzy logic , the researcher develops a fuzzy decision tree based network forensics system to aid an investigator in analyzing computer crime in network environments and automatically extract digital evidence . at the end of the paper , the experimental comparison results between our proposed method and other popular methods are presented . experimental results show that the system can classify most kinds of events ( 91 . 16 ? correct classification rate on average ) , provide analyzed and comprehensible information for a forensic expert and automate or semi - automate the process of forensic analysis 网络取证是对现有网络安全体系的必要扩展,已日益成为研究的重点.但目前在进行网络取证时仍存在很多挑战:如网络产生的海量数据;从已收集数据中提取的证据的可理解性;证据分析方法的有效性等.针对上述问题,利用模糊决策树技术强大的学习能力及其分析结果的易理解性,开发了一种基于模糊决策树的网络取证分析系统,以协助网络取证人员在网络环境下对计算机犯罪事件进行取证分析.给出了该方法的实验结果以及与现有方法的对照分析结果.实验结果表明,该系统可以对大多数网络事件进行识别(平均正确分类率为91 . 16 ? ) ,能为网络取证人员提供可理解的信息,协助取证人员进行快速高效的证据分析