Примеры использования Discriminant analysis на Английском языке и их переводы на Русский язык
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The method of linear discriminant analysis.
Discriminant analysis is used when groups are known a priori unlike in cluster analysis. .
Logistic regression and discriminant analysis.
In the overall discriminant analysis, however, body mass did not make a positive contribution to the multivariate distance.
Experimental data were studied by factorial and discriminant analysis.
The original dichotomous discriminant analysis was developed by Sir Ronald Fisher in 1936.
In order to determine these parameters should be used discriminant analysis.
Statistical analysis were used cluster and discriminant analysis, chi-square test for contingency tables, sign test G.
Considering the instantiation of the diagnostics,the author stresses the necessity of the profound discriminant analysis.
Keywords: metabolic syndrome; discriminant analysis; oxidative stress.
A mathematical model for classification of enterprises to assess the financial condition based on discriminant analysis.
Supervised classification based on discriminant analysis(Statistica 7.0) was used.
Discriminant analysis works by creating one or more linear combinations of predictors, creating a new latent variable for each function.
Perfection of process of state financial audit on the basis of discriminant analysis(p. 161- 163).
Glanbia Nutritionals, UK explain how discriminant analysis adds a valuable layer of security to their production process.
Knysh, Ilya V.(2011)“Perfection of process of state financial audit on the basis of discriminant analysis.” Business Inform 9:161- 163.
Discriminant analysis shown well group definition according to degree of activity, and demonstrated significant contribution of every finding to integral index.
For construction of mathematical models of relapse prognosis after HIFU of prostates two methods of mul-tifactorial analysis of the data have been used: the discriminant analysis and logistical regress.
The results of correlation and discriminant analysis showed that the thought processes is associated with components of intelligence in solving problems.
It is closely related to Hotelling's T-square distribution used for multivariate statistical testing andFisher's Linear Discriminant Analysis that is used for supervised classification.
It has been suggested, however, that linear discriminant analysis be used when covariances are equal, and that quadratic discriminant analysis may be used when covariances are not equal.
However, ANOVA uses categorical independent variables anda continuous dependent variable, whereas discriminant analysis has continuous independent variables and a categorical dependent variable i.e. the class label.
According to discriminant analysis of biochemical indices there was developed a prognostic model enabling to refer an experimental subject either to a group of patients with metabolic syndrome or to healthy people.
EEG patterns evoked by motor imagery are recognized by the classifier based on linear discriminant analysis that uses the features identified by spatial filtering applying CSP method for all types of commands pairwise.
Discriminant analysis is also different from factor analysis in that it is not an interdependence technique: a distinction between independent variables and dependent variables(also called criterion variables) must be made.
Recognition was performed by the classifier based on linear discriminant analysis using the features identified by spatial filtering with CSP method[27] for all types of commands pairwise.
Discriminant analysis showed that the study of quantitative structure of the thyroid gland there may be cases of erroneous inclusion in the theoretical option groups, however, the study of the entire set of indicators observed a 100% correct distribution of cases by groups of pathology.
Feature extraction and dimension reduction can be combined in one step using principal component analysis(PCA),linear discriminant analysis(LDA), canonical correlation analysis(CCA), or non-negative matrix factorization(NMF) techniques as a pre-processing step followed by clustering by K-NN on feature vectors in reduced-dimension space.
Linear discriminant analysis(LDA) is a generalization of Fisher's linear discriminant, a method used in statistics, pattern recognition and machine learning to find a linear combination of features that characterizes or separates two or more classes of objects or events.
The psychological and mathematical discriminant analysis enables to define intrapsychic discrimination markers of different person's self-relation measure over the range"adequate" to"inadequate.