Eigenbeats LLC

Japan

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G06F 18/27 - Regression, e.g. linear or logistic regression 2
G06N 20/00 - Machine learning 2
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1.

INFORMATION PROCESSING METHOD, PROGRAM, AND INFORMATION PROCESSING DEVICE

      
Application Number JP2024023092
Publication Number 2025/028090
Status In Force
Filing Date 2024-06-26
Publication Date 2025-02-06
Owner EIGENBEATS LLC (Japan)
Inventor Nakanishi, Takafumi

Abstract

The purpose of the present invention is to provide an information processing method and the like that assist a user in interpreting the behavior of a generated machine learning model. In this information processing method, a computer performs a process for: associating and recording explanatory data vectors xn input to an existing machine learning model (21) and objective data vectors yn output from the machine learning model (21), as a plurality of pairs; calculating an interpretation matrix A†, which is the vector product of an explanatory matrix X obtained by arranging a plurality of sets of explanatory data vectors xn, and a generalized inverse matrix of an objective matrix Y obtained by arranging objective data vectors yn in an order corresponding to the order of the explanatory data vectors X; and outputting charts (41, 42, 43) for the interpretation matrix A†.

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2.

INFORMATION PROCESSING METHOD, PROGRAM, AND INFORMATION PROCESSING DEVICE

      
Application Number JP2024023287
Publication Number 2025/028098
Status In Force
Filing Date 2024-06-27
Publication Date 2025-02-06
Owner EIGENBEATS LLC (Japan)
Inventor Nakanishi, Takafumi

Abstract

Provided is an information processing method or the like for assisting in understanding of explanatory data created using an XAI technology. In this information processing method, a computer executes a process for: acquiring explanatory data relating to a learning model (22) that receives input of an explanation data vector xn and outputs a target data vector yn, the explanatory data being created using an XAI technology that describes the behavior of the learning model (22); inputting a prompt including the explanatory data to a language model (24); and outputting an explanation from the language model (24).

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