Feature selection method, device, equipment and storage medium based on machine learning
A feature selection method and machine learning technology, applied in the computer field, can solve problems such as low efficiency, and achieve the effect of improving efficiency, improving classification accuracy and generalization ability
Active Publication Date: 2021-07-30
武汉众邦银行股份有限公司
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[0003] The main purpose of the present invention is to propose a feature selection method, device, equipment and storage medium based on machine learning, aiming to solve the technical problem of low efficiency of traditional credit scoring technology
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[0052] It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.
[0053] refer to figure 1 , figure 1 It is a schematic structural diagram of a feature selection device based on machine learning in the hardware operating environment involved in the solution of the embodiment of the present invention.
[0054] Such as figure 1As shown, the feature selection device based on machine learning may include: a processor 1001 , such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002 , a user interface 1003 , a network interface 1004 , and a memory 1005 . Wherein, the communication bus 1002 is used to realize connection and communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a button, and the optional user interface 1003 may also include a standard wired interface and a wireless...
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The invention discloses a feature selection method, device, device and storage medium based on machine learning. The method includes: acquiring user transaction data and a preset reference feature selection model; extracting reference feature information in the transaction data Perform feature selection on the reference feature information through the reference feature selection model; score the reference feature selection model according to the selected reference feature information to obtain a model scoring result; select target features according to the model scoring result Select the model, use the reference feature information selected by the target feature selection model as the target feature information, and then select the optimal feature selection model for feature selection through the combination of multiple models, which has great advantages compared with the single variable selection method The efficiency improvement has significantly improved the classification accuracy and generalization ability of the model for variable selection.
Description
technical field [0001] The present invention relates to the field of computer technology, in particular to a feature selection method, device, equipment and storage medium based on machine learning. Background technique [0002] Since the rapid development of Internet technology, online loans have grown by leaps and bounds. While the number of borrowers has increased, the proportion of malicious loans has also risen sharply, and the data collected by online loans has far more non-financial characteristics than financial characteristics, data sample size and structural complexity. Far beyond the past, traditional scorecard feature selection is usually based on a single algorithm to manually select features, such as the Weight of Evidence (WOE) value, which is labor-intensive and inefficient. Contents of the invention [0003] The main purpose of the present invention is to propose a feature selection method, device, equipment and storage medium based on machine learning, ai...
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IPC IPC(8): G06K9/62G06N20/00
CPCG06N20/00G06F18/21G06F18/23
Inventor 陈刚兰翔钟磊
Owner 武汉众邦银行股份有限公司