Heterogeneity data set anomaly detection method and computer readable storage medium

Abstract

The invention discloses a heterogeneity data set anomaly detection method and a computer readable storage medium. According to the invention, several unused classification indexes are selected from apreset classification index set; index threshold segmentation processing is performed on the heterogeneous data set based on the selected classification indexes; segmented and classified data subsetsare generated under the selected classification indexes; anomaly detection is carried out on each data subset; that is to say, index threshold segmentation processing is performed on the data under the classification indexes based on the selected classification indexes to obtain a plurality of data subsets under the selected classification indexes, and anomaly detection is performed on the data subsets so as to accurately perform anomaly detection on the high-dimensional label-free heterogeneous data set.

Description

Technical field [0001] The present invention relates to the field of computer technology, in particular to an abnormality detection method for heterogeneous data sets and a computer-readable storage medium. Background technique [0002] Currently, statistical hypothesis testing and isolated forest methods are used to detect anomalies in data sets. Specifically, statistical hypothesis testing requires the assumption that the data obey a certain distribution, which is only applicable to one-dimensional data, while isolated forests need to be randomized every time Choose dimensions and thresholds to segment the data set, until finally each set has only one data, which constitutes an isolated tree. The less the number of segmentation, the higher the score of the data outlier. However, because the anomaly detection thresholds of heterogeneous data sets are different, the existing statistical hypothesis tests and isolated forest methods cannot detect anomalies in heterogeneous data set...

AI Technical Summary

Problems solved by technology

[0003] The present invention provides an anomaly detection method for a heterogeneous data set and a computer-readable storage medium to solve the problem in the prior art that the anomaly detection of a heterogeneous data set cannot be performed well

Images