Continuous missing value filling method, data analysis device, terminal and storage medium

Abstract

The invention discloses a continuous missing value filling method, a data analysis device, a data analysis terminal and a computer readable storage medium. The continuous missing value filling methodcomprises the steps that if it is detected that continuous missing values exist in a target time sequence collected on the basis of a preset time interval, collecting all sequence characteristic values from all time sequence samples according to the preset time interval, so that a characteristic data sequence of all the time sequence samples is generated; Performing anomaly detection calculation on each feature data sequence to determine normal data sequences in all the feature data sequences; Obtaining corresponding target time points of the continuous missing value in a target time sequence,and obtaining sequence characteristic values on all the target time points in all the normal data sequences; And carrying out mean value calculation on all sequence characteristic values on each target time point, and taking the characteristic mean value as a filling reference value of the continuous missing value of the corresponding target time point. The data authenticity of the time sequenceis improved.

Description

technical field [0001] The present invention relates to the technical field of data analysis, in particular to a method for filling continuous missing values, a data analysis device, a data analysis terminal and a computer-readable storage medium. Background technique [0002] In real life, people will make statistics on the collected index data. Usually, the continuous change of index data can reflect a historical trend and play a role in predicting the subsequent trend. However, during the statistical process of indicator data, some accidents often occur, such as the inability to continue collecting statistical indicator data during the period of system failure or equipment replacement, resulting in continuous missing values ​​in the indicator data in this continuous time series. However, the existing uniform mean filling will cause the filling value to not conform to the distribution of the time series itself, and the moving mean filling will introduce abnormal data value...

AI Technical Summary

Problems solved by technology

[0003] The main purpose of the present invention is to provide a method for filling continuous missing values, a data analysis device, a data analysis terminal, and a computer-readable storage medium, aiming at solving the problem that the traditional single-point missing value filling method is easy to fill and calculate for continuous missing values. The introduction of abnormal data values ​​makes the calculated filling value offset larger, resulting in a technical problem that reduces the authenticity of the data

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