Abnormal data detection method, electronic equipment and storage medium

Abstract

The invention discloses an abnormal data detection method, electronic equipment and a storage medium. The abnormal data detection method comprises the steps: determining a first reachable distance from each second point to a first point based on a first distance between each second point and the first point in a k neighborhood of the first point in a data point set and a k distance of each second point, wherein the data point set is obtained by converting business data of a set type, and each first reachable distance is different from the corresponding first distance and the corresponding k distance; determining a local outlier factor of the first point based on the local reachable density of the first point and the local reachable density of each second point in the k neighborhood of the first point, wherein the local reachable density of the first point represents the reciprocal of the mean value of all the first reachable distances; under the condition that the determined local outlier factor is greater than a set threshold value, determining the first point as an abnormal point; and outputting a business data detection result based on the determined abnormal point.

Description

technical field [0001] The invention relates to the technical field of computers, in particular to an abnormal data detection method, electronic equipment and storage media. Background technique [0002] With the development of computer technology, more and more technologies, such as blockchain (Blockchain), big data, distributed and other technologies are applied in the financial field, and the traditional financial industry is gradually transforming into financial technology. However, due to financial The security and real-time requirements of the industry, and financial technology also put forward higher requirements for technology. In the field of financial technology, in the scenario where the local outlier factor (LOF, Local Outlier Factor) algorithm is used to detect abnormal data, since the reachable distance from point O to point P is the k-distance (k distance) of point O and the distance from point O to The maximum value in the first distance of point P. Therefor...

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Problems solved by technology

[0004] In view of this, an embodiment of the present invention provides an abnormal data detection method, an electronic device, and a storage medium to solve the problem of local outliers based on point P caused by inaccurate local reachable density of point P in the related art. The technical problem that the detection result of the abnormal data obtained by the factor is inaccurate

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