Method for obtaining the regression relationship between the dependant variable and the independent variables during data analysis
A regression relationship and data analysis technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve problems such as difficult to achieve analysis efficiency, time-consuming and labor-intensive efficiency, data area difference analysis, etc., to improve analysis and accuracy , the effect of the simplified process
Inactive Publication Date: 2017-05-10
G CLOUD TECH
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The whole process is time-consuming, labor-intensive and inefficient, and the amount of input data, for all the data, the dependent variable and the independent variable may have different causal relationships. Directly using traditional methods cannot perform differential analysis of data regions, and it is difficult to achieve accurate results. Analysis efficiency
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[0034] The invention standardizes the data by analyzing the dependent variable and a plurality of independent variables input by the user, and simultaneously saves the data standardization results of each dependent variable and independent variable for subsequent data prediction; the data is then classified from a horizontal perspective. , so as to analyze similar data features, and then select longitudinal independent variables from similar data features. By calling the relevant linear analysis algorithm, the causal relationship is obtained, and the calculated and analyzed results are compared with the actual results. The optimal relationship between some independent variables and dependent variables is obtained, and the final optimal result is displayed to the user for final selection. Using this method can efficiently obtain the optimal causal relationship with the dependent variable from multiple independent variables. , which can greatly improve the efficiency of obtaining...
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The invention relates to the data analyzing and data processing field and more particularly, to a method for obtaining the regression relationship between the dependant variable and the independent variables during data analysis. The method comprises the following steps: through the analysis of the dependant viable and a plurality of independent variables inputted by a user, conducting standard processing to the data; then, classifying the data followed by the analyzing of similar data characteristics; selecting from the similar data characteristics the independent variables; through the calling of a related linear analyzing algorithm, obtaining a causal relationship; comparing the result obtained from calculation and analysis with the actual result; analyzing the best relationship between some independent variables and the dependant variable; and finally, displaying the best result to a user as a finalized choice. The method of the invention solves the problems in the prior art that discriminate analysis cannot be made for the data regions and that accurate analyzing efficiency is difficult to reach. The method and system could be used to obtain the regression relationship between the dependant variable and the independent variables.
Description
technical field [0001] The invention relates to the technical field of data analysis and processing, in particular to a method for obtaining the regression relationship between a dependent variable and an independent variable in data analysis. Background technique [0002] In the process of data analysis, regression analysis is a method that is often used. The traditional regression process requires the user to select the independent variable and dependent variable according to the relationship of a related model, input the data manually and analyze the final results one by one, and then check the regression coefficient, The accuracy of the independent variable and the actual dependent variable. When the relationship between multiple independent variables and dependent variables cannot be clearly viewed, the user needs to perform operations one by one. The whole process is time-consuming, labor-intensive and inefficient, and the amount of input data, for all the data, the ...
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CPCG06F18/23211
Inventor 郑锐韬李勇波孙傲冰季统凯
Owner G CLOUD TECH