Feature selection method and device, readable storage medium and computer program product
A feature selection method and feature selection technology, applied in the field of machine learning of financial technology, can solve problems such as low feature selection accuracy
Pending Publication Date: 2021-05-25
WEBANK (CHINA)
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[0004] The main purpose of this application is to provide a feature selection method, device, readable storage medium and computer program product, aiming to solve the technical problem of low feature selection accuracy in the prior art
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[0035] It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.
[0036] The embodiment of the present application provides a feature selection method. In the first embodiment of the feature selection method of the present application, refer to figure 1 , the feature selection method is applied to the first device, and the feature selection method includes:
[0037] Step S10, obtaining the multi-class label data set corresponding to the sample data set, and generating each binary class label data corresponding to the multi-class label data set;
[0038] In this embodiment, it should be noted that the feature selection method is applied to a vertical federated learning scenario, and the sample data set is a sample set generated by aligning samples between the first device and the second device, and the sample data set is at least Including a multi-classification sample, the mult...
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The invention discloses a feature selection method and device, a readable storage medium and a computer program product, the feature selection method is applied to a first device, and the feature selection method comprises the following steps: obtaining a multi-classification tag data set corresponding to a sample data set, and generating each piece of dichotomy tag data corresponding to the multi-classification tag data set; sending each piece of dichotomy label data to a second device, so that the second device generates a label statistical result corresponding to each piece of dichotomy label data based on each piece of dichotomy label data, a sample binning result corresponding to a generated target feature and a preset public sample ID; receiving each label statistical result, and calculating a feature evaluation value corresponding to each piece of dichotomy label data based on each label statistical result; and performing feature selection on the target feature according to each feature evaluation value to obtain a feature selection result. The technical problem of low feature selection accuracy is solved.
Description
technical field [0001] The present application relates to the technical field of machine learning in financial technology (Fintech), and in particular to a feature selection method, device, readable storage medium and computer program product. Background technique [0002] With the continuous development of financial technology, especially Internet technology finance, more and more technologies (such as distributed, artificial intelligence, etc.) The industry also has higher requirements for the distribution of to-do items. [0003] With the continuous development of computer technology, the application of machine learning models is becoming more and more extensive. Usually, feature selection is required before modeling. At present, in the multi-classification scenario of vertical federation, each participant in vertical federation usually unilaterally Perform feature selection, for example, exclude features with small standard deviations through statistical feature values,...
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IPC IPC(8): G06K9/62
CPCG06F18/211G06F18/241
Inventor 谭明超马国强范涛陈天健杨强
Owner WEBANK (CHINA)