公开(公告)号：US20240119357A1

公开(公告)日：2024-04-11

申请号：US18276809

申请日：2021-02-25

Applicant: NEC Corporation

Inventor： Keita SAKUMA ,  Tomoya SAKAI ,  Yoshio KAMEDA ,  Hiroshi TAMANO

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Provided are an analysis device, an analysis method, and a program capable of easily identifying a factor of a prediction error in prediction using a prediction model on the basis of various viewpoints. An analysis device (1) includes: a metric evaluation unit (2) that calculates and evaluates a plurality of types of metrics with respect to a prediction model, data of explanatory variables used in the prediction model, or data of target variables used in the prediction model; and a factor identification unit (3) that identifies a factor of an error in prediction by the prediction model according to a combination of evaluation results of the plurality of types of metrics.

公开(公告)号：US20240211367A1

公开(公告)日：2024-06-27

申请号：US18539410

申请日：2023-12-14

Applicant: NEC Corporation

Inventor： Keita SAKUMA ,  Ryuta Matsuno

IPC: G06F11/34 ,  G06F11/30

CPC classification number: G06F11/3409 ,  G06F11/3051

Abstract: In a pipeline evaluation device, a data acquisition means acquires time series data. A pipeline execution means executes a pipeline using the data being acquired, and generates an execution result. A metric calculation means calculates an evaluation metric using the execution result acquired by executing the pipeline by using the execution result, and outputs an evaluation result.

公开(公告)号：US20250094308A1

公开(公告)日：2025-03-20

申请号：US18559113

申请日：2023-03-06

Applicant: NEC Corporation

Inventor： Ryuta MATSUNO ,  Keita SAKUMA

IPC: G06F11/34 ,  G16H50/20

Abstract: In order to provide a model evaluation method in which a plurality of groups are considered, an information processing device according to the present invention includes a data acquisition means that acquires at least one condition for evaluation data of a machine learning model, a performance calculation means that calculates a performance index of the machine learning model and a performance index of the machine learning model after being updated using a data set specified for each of the at least one condition, and an index calculation means that calculates a deterioration index of a performance of the machine learning model based on the performance indexes before and after the machine learning model is updated.

公开(公告)号：US20250077964A1

公开(公告)日：2025-03-06

申请号：US18579531

申请日：2023-08-23

Applicant: NEC Corporation

Inventor： Ryuta MATSUNO ,  Keita SAKUMA

IPC: G06N20/00

Abstract: A model evaluation device 100 of the present disclosure includes a generation unit 121 that generates a plurality of second machine learning models that are different from a first machine learning model subject to performance evaluation, and an evaluation unit 122 that evaluates the first machine learning model on the basis of prediction labels that are output by inputting the same data to the first machine learning model and to each of the second machine learning models. Therefore, the model evaluation device 100 is able to assist decision making by a user.

公开(公告)号：US20250103422A1

公开(公告)日：2025-03-27

申请号：US18578803

申请日：2023-08-23

Applicant: NEC Corporation

Inventor： Keita SAKUMA ,  Ryuta Matsuno

IPC: G06F11/07

Abstract: An information processing device 100 of the present disclosure can assist decision-making by a user by including: an error calculation unit 121 that calculates a prediction error which is a difference between a prediction value which is output obtained when an explanatory variable of subject data is input to a prediction model and an objective variable of the subject data; an index calculation unit 122 that calculates, on a basis of data that can be used for calculating the prediction error, an index for evaluating an amount of contribution of at least one of the explanatory variable of the subject data, the objective variable of the subject data, and the prediction model to the prediction error; and a contribution calculation unit 123 that calculates the amount of contribution on a basis of the prediction error and the index.

公开(公告)号：US20240028912A1

公开(公告)日：2024-01-25

申请号：US17863338

申请日：2022-07-12

Applicant: NEC CORPORATION

Inventor： Vivek BARSOPIA ,  Yoshio KAMEDA ,  Tomoya SAKAI ,  Keita SAKUMA ,  Ryuta MATSUNO

IPC: G06N5/02

CPC classification number: G06N5/022

Abstract: Predictively robust models are trained by embedding a distribution of each temporal data set among a plurality of temporal data sets into a feature vector, predicting a future feature vector of a distribution of a future data set, based on the feature vector of each temporal data set among a plurality of temporal data sets, creating the future data set from the future feature vector, perturbing the future data set to produce a plurality of perturbed future data sets, and training a learning function using the future data set and each perturbed future data set to produce a model.