Characteristic variable analysis method and device, computer equipment and storage medium
A technology of characteristic variables and analysis methods, applied in computer security devices, computing, complex mathematical operations, etc., can solve problems such as data leakage, difficulty in ensuring data security, and achieve the effect of protecting data privacy
Pending Publication Date: 2022-01-14
PING AN TECH (SHENZHEN) CO LTD
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[0004] The purpose of the embodiments of the present application is to propose a characteristic variable analysis method, device, computer equipment, and storage medium to solve the technical problems of data leakage risks that may exist in the existing characteristic variable analysis methods and difficulty in ensuring data security
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[0060] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field of the application; the terms used herein in the description of the application are only to describe specific embodiments The purpose is not to limit the present application; the terms "comprising" and "having" and any variations thereof in the specification and claims of the present application and the description of the above drawings are intended to cover non-exclusive inclusion. The terms "first", "second" and the like in the description and claims of the present application or the above drawings are used to distinguish different objects, rather than to describe a specific order.
[0061] Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The occurrenc...
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The invention discloses a characteristic variable analysis method and device, computer equipment and a storage medium, and belongs to the technical field of data analysis and processing. According to the method, firstly, the feature data and the feature tags stored in different clients are binned, then the weighted average value of the feature data is calculated to obtain the first weighted average value, the weighted average value of the feature tags is calculated to obtain the second weighted average value, and a linear regression equation is constructed based on the first weighted average value and the second weighted average value; and a mean square error and a total sum of squares of the target characteristic variable are calculated based on the linear regression equation, a decision coefficient of the target characteristic variable is calculated based on the mean square error and the total sum of squares, and the target characteristic variable is evaluated based on the decision coefficient. In addition, the invention also relates to a block chain technology, and the feature data and the feature tags can be stored in a block chain. According to the method and the device, multi-client joint variable analysis can be realized under the condition of protecting data privacy.
Description
technical field [0001] The present application belongs to the technical field of data analysis and processing, and in particular relates to a characteristic variable analysis method, device, computer equipment and storage medium. Background technique [0002] The existing federated learning is mainly aimed at the modeling part, but in the actual process, due to the large number of data features and the uneven quality of the features, the model training rate is slow and the effect is not good. In response to this situation, the traditional method is to analyze the features before modeling. After selecting effective features, modeling can improve the training speed and improve the accuracy of the model. [0003] However, the existing feature variable analysis methods usually need to transfer the features or labels to the same client when the features or labels are not on the same client, and then the variable analysis can be performed, but in federated learning, it is necessar...
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Login to View More IPC IPC(8): G06F17/18G06F17/11G06F21/62
CPCG06F17/18G06F17/11G06F21/6245
Inventor 黄晨宇王健宗
Owner PING AN TECH (SHENZHEN) CO LTD