Missing data-based sample analysis method and device, electronic equipment and medium

Abstract

The invention relates to a big data technology, and discloses a missing data-based sample analysis method, which comprises the following steps: obtaining a missing data set and a corresponding label value, calculating the saturation of missing data dimensions in the missing data set, selecting the missing data dimensions of which the saturation is greater than a preset saturation, and generating afeature dimension list; calculating correlation coefficients of missing data dimensions and label values in the feature dimension list, selecting missing data dimensions of which the correlation coefficients are greater than a preset correlation coefficient, and modeling the selected missing data dimensions to generate a missing data insensitive model; and performing data analysis on the to-be-analyzed sample data set by utilizing the missing data insensitive model to obtain an analysis result. The invention further provides a missing data-based sample analysis device, electronic equipment and a storage medium. In addition, the invention also relates to a blockchain technology, and the selected missing data dimension can be stored in the blockchain. According to the invention, the phenomenon of inaccurate sample analysis caused by missing data can be solved.

Description

Technical field [0001] The present invention relates to big data technology, in particular to a sample analysis method, device, electronic equipment and computer readable storage medium based on missing data. Background technique [0002] One difficulty of current real-world data mining is the lack of data. For example, for data based on online or paper questionnaires, respondents often skip specific questions, resulting in incomplete answers to the returned questionnaire. At this time, there will be missing features in this survey sample. [0003] At present, whether it is to fill in missing features or directly discard this missing sample, it has its own shortcomings: among them, for missing feature filling, there is no guarantee that the filled value can truly reflect the missing value; for missing sample, it is discarded In other words, discarding missing samples will result in a waste of information. [0004] Therefore, whether it is filling in missing features or directly dis...

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Problems solved by technology

[0005] The present invention provides a sample analysis method, device, electronic equipment and computer-readable storage medium based on missing data, the main purpose of which is to solve the inaccurate phenomenon of sample analysis caused by missing data

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