Full Article: PDF
Scientific Object Identifier: http://s-o-i.org/1.1/TAS-06-74-75
DOI: https://dx.doi.org/10.15863/TAS.2019.06.74.75
Language: Russian
Citation: Zhanatauov, S. U. (2019). Coefficients of regression, containing mathematically introduced and cognitively extractabled knowledge. ISJ Theoretical & Applied Science, 06 (74), 613-622. Soi: http://s-o-i.org/1.1/TAS-06-74-75 Doi: https://dx.doi.org/10.15863/TAS.2019.06.74.75 |
Pages: 613-622
Published: 30.06.2019
Abstract: The article developed a variant of the Inverse Model of Multiple Linear Regression Analysis (OM MLRA with given regression coefficients =(?1,…,?n-1)T,Z+2=Z+1?, Z+mn=[Z+1?Z+2], containing mathematically int of produced and cognitively extracted knowledge With the use of equalities from Inverse Model the Principal Component Analysis (IM PCA) solved a New Inverse Generalized Problem of Multiple Linear Regression Analysis (IGM MLRA) of statistical modeling of n-1 correlated z-variables, 1 z–variable: Z+mn=[Z+1?Z+2],Z+2=Z+1?, satisfying all equations and relations in DM MLRA: (Z+1,Z+2)=>(R-111,R12,?). Simulated (?,C+11)-–samples Z+mn=[Z+1?Z+2], Z+2=Z+1?, in the presence of a partition, and the extraction of knowledge - without partitioning the set of z – variables. The input parameters of the IGP of MLRA are the vector ?=(?1,…,?n-1)T and the matrix of eigenvectors C+11. The numerical algorithms were tested using the example of modeling a multidimensional (?,C+11)-sample of z –variables (with n=6). The designated vector ?=(?1…,?6)T regression coefficients was used. A description of the reverse process of extracting the knowledge entered using cognitive modeling will be published in another article.
Key words: mathematically introduced, cognitively extracted knowledge.
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