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Method and device for evaluating model interpretation tool

A technology for evaluating models and models, applied in the field of machine learning, to solve problems such as the lack of multiple model interpretation tools

Active Publication Date: 2020-04-14
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is still no method that can be applied to multiple model interpretation tools at the same time

Method used

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  • Method and device for evaluating model interpretation tool
  • Method and device for evaluating model interpretation tool
  • Method and device for evaluating model interpretation tool

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Experimental program
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Embodiment Construction

[0066] Embodiments of this specification will be described below with reference to the accompanying drawings.

[0067] figure 1 A schematic diagram of a system 100 for evaluating model interpretation tools according to an embodiment of the present specification is shown. Such as figure 1 As shown in , the system 100 includes a first sample processing unit 11 , a black box model 12 , a model interpretation tool 13 , a second sample processing unit 14 , an evaluation unit 15 and a calculation unit 16 . The black box model 12 is, for example, a non-self-explanatory model that is expected to be explained by the model interpretation tool 13, such as various complex neural network models, etc. The neural network model is due to its multi-layer, multi-neuron complex structure, The importance of sample features cannot be explained by its individual parameters or network structure. The black box model 12 can be trained through multiple training samples related to a specific business...

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Abstract

The embodiment of the invention provides a method and device for evaluating a model interpretation tool, and the method comprises the steps: training a first model by adopting a plurality of first training samples so as to obtain the first model with a first parameter group; acquiring the first performance value of the first model with the first parameter group based on a plurality of test samples; based on the plurality of first training samples and the first parameter group, obtaining importance sequences of a plurality of features through a model interpretation tool; replacing the feature values of the features except the first n features of the importance sequence in each first training sample with the same predetermined value to obtain a plurality of second training samples; trainingthe first model by using the plurality of second training samples to obtain a first model with a second parameter group; acquiring the second performance value of the first model with the second parameter group based on the plurality of test samples; and calculating a difference value between the first performance value and the second performance value for evaluating the model interpretation tool.

Description

technical field [0001] The embodiments of this specification relate to the technical field of machine learning, and more specifically, to a method and device for evaluating model interpretation tools. Background technique [0002] Machine learning is currently being used in various fields such as retail, technology, healthcare, science, and many more. A machine learning model essentially fits a complex function to the relationship between the data and the target. The machine learning model is very different from some simple rules. The rules clarify the relationship between data and targets, but the machine learning model is a black box with only input and output, and does not understand the internal mechanism. In some fields, especially in finance, such as insurance, banking, etc., data scientists often end up having to use more traditional and simpler machine learning models (linear models or decision tree models). However, although this type of simple model can provide a...

Claims

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Application Information

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IPC IPC(8): G06Q40/02G06Q30/02G06N3/04G06N3/08
CPCG06Q30/0201G06N3/084G06N3/045G06Q40/03
Inventor 方军鹏唐才智
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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