Literatures indicate that logit model , logistic model , probit model , mlr , cluster model , option model , proportion risk model , and discriminant analysis are the main effective methods and models when researching the determinants of residential mortgage default risk 通过梳理文献发现, logit模型、 logistic模型、 probit模型、多元线性回归、聚类模型、期权模型和比例风险模型、判别分析是研究个人住房抵押贷款违约风险影响因素时采用的主要方法和模型。
Whereas the importance of market segmentation in mc , this thesis research emphatically the application of matlab - based mathematic statistics methods such as regression analysis , clustering analysis , discriminant analysis and so on . the research can contribute to mc theoretically and practically 鉴于市场细分在大规模定制生产模式中的重要性,本文重点研究了基于matlab的数理统计方法,如回归分析,聚类分析,判别分析等在大规模定制的市场细分中的应用。
In this paper the technology of human identification based on gait is mainly concerned . we analyze some gait recognition methods that we have known and probed into the gait features extracting method especially . and a new gait recognition method based on kernel - based fisher discrimination analysis is proposed 本文提出了一种基于核函数的fisher判别分析( kfda )进行步态识别的算法。在文中还分析和研究了现有的步态识别的各种方法,并介绍了一种提取步态特征的方法。
To retrieval directly information with images , by using the face detection technique based on the gravity - center template matching method and the face recognition technique based on methods of the principal component analysis and the linear discriminative analysis 摘要为了能直接通过图像检索自己所需要的信息,提出了一种直接根据人脸图像来检索信息的技术,采用基于重心模板匹配的人脸检测技术与主成分分析方法、线性判别分析方法相结合的人脸识别技术设计并实现了一个人脸图像检索系统。
The correctness is over 99 % . ( 5 ) shape features studied were aspect , first invariant central moment , elongatedness , roundness , circularity and thickness . aspect and first invariant central moment are the most effective shape features for identifying monocotyledonous weed from dicotyledonous weed , and the correctness was 93 % ( 4 )利用修正的色度公式,由判别分析法确定色度阈值,对杂草图像进行阈值分割,能够有效地识别植物与非植物背景,正确识别率在99以上,但色度的计算量大于过绿特征的计算量,不利于杂草识别速度的提高。
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。