Title:
INFORMATION PROCESSING DEVICE, PREDICTION DEVICE, MACHINE-LEARNING METHOD, AND TRAINING PROGRAM
Document Type and Number:
WIPO Patent Application WO/2024/029261
Kind Code:
A1
Abstract:
Even when k is set to a large value when determining a determination list by which a prediction result is calculated on the basis of prediction values of highest k determination rules (k is a natural number equal to or greater than 2) in which observation satisfies a condition, in order not to increase a processing time or memory use amount which is required to determine the determination list, this information processing device 1 comprises: a prediction unit 11 which calculates, for each training example included in a training example set, a prediction result on the basis of highest k prediction values of which the training examples satisfy the conditions among the determination rules included in the determination list; and a list determination unit 12 which determines the determination list to be output by repeating an update process in which variables representing the determination list are updated until values of an objective function, which includes error terms that indicate errors in the prediction results, satisfy prescribed conditions, wherein the variables include a variable that indicates, among the determination rules in which the conditions are satisfied, a determination rule of which the priority to be used for prediction is k. To this end, the information processing device 1 can promote better decision making by a user on the basis of the determination rules of which the priorities are higher.
Inventors:
SASAKI YOICHI (JP)
OKAJIMA YUZURU (JP)
OKAJIMA YUZURU (JP)
Application Number:
PCT/JP2023/024893
Publication Date:
February 08, 2024
Filing Date:
July 05, 2023
Export Citation:
Assignee:
NEC CORP (JP)
International Classes:
G06N20/00
Domestic Patent References:
| WO2020059136A1 | 2020-03-26 | |||
| WO2022029821A1 | 2022-02-10 |
Other References:
MATA KOTA, KANAMORI KENTARO, ARIMURA HIROKI: "Computing the Collection of Good Models for Rule Lists", ARXIV (CORNELL UNIVERSITY), CORNELL UNIVERSITY LIBRARY, ARXIV.ORG, ITHACA, 24 April 2022 (2022-04-24), Ithaca, pages 1 - 16, XP093134731, Retrieved from the Internet [retrieved on 20240226], DOI: 10.48550/arxiv.2204.11285
Attorney, Agent or Firm:
HARAKENZO WORLD PATENT & TRADEMARK (JP)
Download PDF: