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discriminated analysis中文是什么意思

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  • 差别分析

例句与用法

  • A discriminating analysis on the style of critical writing
    意见写作的文体辨析
  • The qualitative discriminating analysis to urban vegetable product pollution state space
    城市蔬菜品种污染状态空间的定性识别分析
  • Data obtained have been analyzed by multivariate statistical analysis methods including tactor and discriminate analysis
    所获数据以多变量统计分析技术的主成分分析法作了统计运行。
  • Thus , traditional credit assessment models , such as financial ratio analysis , multiple discriminate analysis and so on , cannot solve this problem effectively , completely and perfectly
    传统的信用评价模型有财务比率分析、多元判别分析等,但这些模型都不能有效、全面、完整地解决信用评价问题。
  • We use gmdh to set up a forecasting model of chinese listed companies ’ financial crisis by using financial data . we compare the prognosticating effects of 3 models , which are set up according to the following 3 kinds of ways : the discriminate analysis , the logit analysis , and find that the gmdh is more effective way to transform data into knowledge
    将gmdh算法应用于财务数据的挖掘,预测上市公司的财务危机,实证结果表明基于gmdh的上市公司财务预测模型,预测准确率优于判别分析和logit回归分析,显示出gmdh在模型识别和模型推广能力上具有它独特的优越性。
  • Based on the analysis of types and sources of risks that confront commercial banks , the paper first determines the methodology for its research , i . e . mathematical statistics for quantity factors and the fuzzy discriminating analysis for the quality factors . combining the evaluation approaches of the banks in germany and china , the paper gets 13 common indices , and with mathematical statistical method , chooses 4 factors that will influence customer credits : equity capital / total asset , velocity of stock in trade , velocity of total assets and payoff rate of total sale . the four factors with liquidity factor reflect the customer ' s financial characteristics , such as capital structure , operation , earnings and liquidity
    在理论分析的基础上,结合德国和中国有关银行的客户资信评价方法,在得到影响客户信用13个常用指标的基础上,利用数理统计分析方法( t检验、多元判别分析和逐步判别分析等)得出影响客户信用的四个因素:自有资本率、存货周转率、总资产周转率和销售盈利率,他们反映了企业资本结构、经营状况和盈利水平,加入企业的流动性以后,它们决定了客户的财务特征。
  • In the recent 50 years , many models such as multivariate discriminate analysis and neural network come out . however , in our country , financial distress prediction just begins . the main reasons are as follows : one reason is the lack of uniform accountant rule before july 1 , 1993 , the other reason is the difficult of having the financial dates of unlisted companies
    但是,在国内对企业财务困境预测的研究才刚刚起步,并且主要集中在对上市公司财务困境预测的研究上,其主要原因有两点:一是1993年7月1日之前我国并没有实施统一的会计准则,缺乏可靠规范的研究数据;二是非上市公司财务数据的获取十分困难。
  • Moreover , the fuzzy clustering discriminate analysis method for distinguishing and eliminating the gross error of the measurement sample is established . the gross error of the practical measured data is distinguished by use of the method prove the established the gross error distinguishing model practical to the measurement system
    建立了测量样本粗大误差判别和剔除的模糊聚类判别方法,通过对实际测量数据的粗大误差判别,证明了所建立的粗大误差判别模型对测量系统的实用性。
  • Considered the actual situation in china ' s stock exchanges , the author regards “ st ” ( special treatment ) as the sign of “ financial distress ” in this dissertation . by applying fisher ’ s multivariate discriminating analysis and logistic regressive analysis , the author creates two predictive models . the main conclusion of this dissertation are as follow : 1 . the reasons of the corporation financial distress are due to the poor earnings , the lower net cash and the liquidity problem . 2 . the financial ratio indexes of the listed corporation in china include the information of the forecasting financial distress
    随着我国证券市场的日益规范化,根据在客观、公允基础上披露的上市公司的财务报告,通过选择信息含量高的财务指标构建合理的预测模型,获得对那些财务状况出现严重恶化的上市公司的预警信号不仅是可行的,而且还能使债权人避免贷款的高风险,投资者避免或减少投资损失,公司经营者根据这些信号及早采取相应措施。
  • Data mining is defined as the nontrivial extraction of implicit , previously unknown , and potentially useful information from data or known as knowledge - discovery in databases ( kdd ) . to do this , data mining uses computational techniques from statistics , machine learning and pattern recognition such as discriminate analysis , regression method , mathematical programming , decision tree , k - nearest neighbor , artificial neural network etc . although many positive attempts are done , the development and application of personal credit assessment model in chinese bank industry is still in its infancy
    数据挖掘是20世纪90年代后期人工智能和数据库领域兴起的一种数据处理和知识发现( kdd )理论,是从大量的、不完全的、有噪声的、模糊的和随机的实际应用数据中,提取隐含在其中的信息和知识的过程。对数据进行分类和预测是数据挖掘的主要功能。数据挖掘用于信用评估的优势主要在于: ( 1 )能处理和修正实际数据问题,算法模型具有自检
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