Model construction and analysis method and device, electronic equipment and medium

Abstract

The invention provides an analysis method, which comprises the steps of determining an analysis time period in response to a received analysis instruction for a target object, the analysis time periodbeing related to a timestamp of predetermined time series data of the target object; obtaining first time series data of the target object in the analysis time period; obtaining a first time sequencefeature set based on the first time sequence data; at least inputting the first time sequence feature set into a pre-established first analysis sub-model to obtain a first intermediate result; and sending the first intermediate result to the joint platform device, so as to enable the joint platform device to obtain an analysis result based on the first intermediate result and a second intermediate result from a second mechanism server, wherein the second mechanism is a mechanism for joint analysis with the first mechanism. The invention further provides a model construction method, an analysis device, a model construction device, a joint analysis system, electronic equipment and a computer readable storage medium.

Description

technical field [0001] The present disclosure relates to the field of computer technology, and more specifically, to an analysis method, an analysis device, a model construction method, a model construction device, a joint analysis system, electronic equipment, and a computer-readable storage medium. Background technique [0002] In recent years, with the increasing demand for joint establishment of analysis models among different institutions, federated learning technology has developed rapidly. Federated learning can jointly establish analysis models with multiple institutions while meeting the requirements of user privacy protection, data security and government regulations. And apply the model for analysis. [0003] In the process of realizing the concept of the present disclosure, the inventors have found that at least the following problems exist in the related art: [0004] When federated learning technology is used for joint modeling, the two parties involved in the...

AI Technical Summary

Problems solved by technology

[0004] When federated learning technology is used for joint modeling, the two parties involved in the modeling cannot interact with time series data in real time, resulting in the inability to incorporate behavior-sequence-based features into the federated learning model. Only non-behavior sequence features can be used f

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