Method, device and system for estimating causal effect of target variable on result variable

A technology of target variable and variable, which is applied in the field of estimating the causal effect of the target variable on the outcome variable, which can solve the problems of long learning time, inability to determine the direct causal effect, cost, etc.

Pending Publication Date: 2019-07-09
NEC CORP
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0008] According to this causal effect evaluation method in the prior art, it will take a long learning time
In a

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  • Method, device and system for estimating causal effect of target variable on result variable
  • Method, device and system for estimating causal effect of target variable on result variable
  • Method, device and system for estimating causal effect of target variable on result variable

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Embodiment Construction

[0027] Hereinafter, various exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. It should be noted that these drawings and description relate to preferred embodiments as examples only. It should be noted that, from the ensuing description, alternative embodiments of the structures and methods disclosed herein are readily conceivable and may be employed without departing from the disclosed principles of the present disclosure as claimed.

[0028] It should be understood that these exemplary embodiments are given only to enable those skilled in the art to better understand and implement the present disclosure, but not to limit the scope of the present disclosure in any way. In addition, in the drawings, for the purpose of illustration, optional steps, modules, modules, etc. are shown in dashed boxes.

[0029] The terms "including", "comprising" and similar terms used herein should be understood as open-ended t...

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Abstract

The invention discloses a method, a device and a system for estimating the causal effect of a target variable on a result variable. According to the method disclosed by the invention, a related variable set of target variables is determined for a given target variable by utilizing observation data, and the related variable set comprises variables related to the target variable. However, a local causal network comprising the target variable and a variable associated with the target variable is learned with observational data relating to the target variable and the variable associated with the target variable, resulting in a learned local causal network of the target variable. Then, at least one of a direct causal effect and a total causal effect of the target variable to the result variableis determined according to a relationship between the target variable indicated in the learned local causal network of the target variable and the result variable. By utilizing the method and the device, the time required for evaluating the causal effect can be greatly shortened, the efficiency of evaluating the causal effect is remarkably improved, and quantitative evaluation is given for the causal effect.

Description

technical field [0001] The present disclosure relates to the technical field of data mining, and more particularly to a method, device and system for estimating the causal effect of a target variable on an outcome variable. Background technique [0002] In the era of big data, a large amount of data can be obtained through various data collection channels. Through data analysis and mining of these data, a lot of useful information can be obtained. However, in many application fields, people often only see the appearance of the system, but cannot gain insight into the complex mechanism and process behind the system, but can only gain an empirical understanding. [0003] Causal structure learning is dedicated to learning and discovering the causal relationship between multiple variables based on systematic observation data, automatically restoring the complex mechanism behind the system, and reproducing the data generation process. At present, causal structure learning techn...

Claims

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Application Information

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IPC IPC(8): G06N5/04
CPCG06N5/041
Inventor 刘春辰刘越何洋波耿直
Owner NEC CORP
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