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Model interpretation method and equipment and readable storage medium

A model and model input technology, applied in neural learning methods, biological neural network models, encryption devices with shift registers/memory, etc., can solve problems such as poor model interpretation effect

Active Publication Date: 2020-09-01
WEBANK (CHINA)
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0004] The main purpose of this application is to provide a model interpretation method, device and readable storage medium, aiming to solve the technical problem of poor model interpretation effect in the prior art

Method used

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  • Model interpretation method and equipment and readable storage medium
  • Model interpretation method and equipment and readable storage medium
  • Model interpretation method and equipment and readable storage medium

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Embodiment Construction

[0080] It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.

[0081] The embodiment of the present application provides a model interpretation method. In the first embodiment of the model interpretation method of the present application, refer to figure 1 , the model interpretation method includes:

[0082] Step S10, obtain the input features of each model corresponding to the preset black box model, and input the prediction data set corresponding to each model input feature into the first hash coding model optimized based on each preset sample category, and the prediction data set Perform hash encoding to obtain the first hash encoding result;

[0083] In this embodiment, it should be noted that the preset black box model is a model obtained by training based on the training data set corresponding to each of the model input features, and the first hash coding model is base...

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Abstract

The invention discloses a model interpretation method and equipment and a readable storage medium. The model interpretation method comprises the following steps of obtaining each model input feature corresponding to a preset black box model, inputting the prediction data set corresponding to each model input feature into a first hash coding model optimized based on each preset sample category; carrying out hash coding on the prediction data set; obtaining a first hash coding result, inputting the prediction data set into a second hash coding model optimized based on each output sample categoryoutput by the preset black box model; and performing hash encoding on the prediction data set to obtain a second hash encoding result, and further determining feature confidence corresponding to eachmodel input feature based on each bit difference degree between the first hash encoding result and the second hash encoding result. The technical problem that the model interpretation effect is pooris solved.

Description

technical field [0001] The present application relates to the artificial intelligence field of financial technology (Fintech), and in particular to a model interpretation method, device and readable storage medium. Background technique [0002] With the continuous development of financial technology, especially Internet technology and finance, more and more technologies (such as distributed, blockchain, artificial intelligence, etc.) Requirements, such as the distribution of corresponding to-do items in the financial industry also have higher requirements. [0003] With the continuous development of computer software and artificial intelligence, the application fields of deep learning are becoming more and more extensive, and the performance of models based on deep learning is getting better and better. However, because the models based on deep learning are all black-box models, it is difficult to accurately Explain under what circumstances the model will fail and be effect...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08H04L9/06
CPCG06N3/08H04L9/0643G06N3/045G06F18/214
Inventor 吴锦和范力欣张天豫
Owner WEBANK (CHINA)
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