Patent ID: 11886990
Assignee: KABUSHIKI KAISHA TOSHIBA
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 4:
5. A classification method comprising;
generating pseudo data by using a generation model, the generation model being learned to generate the pseudo data based on a third loss criterion representing a difference between the pseudo data and a plurality of pieces of training data that include a plurality of pieces of first training data and a plurality of pieces of second training data, the plurality of pieces of first training data being data of a first class among a plurality of classification classes, the plurality of pieces of second training data being data of a second class among the plurality of classification classes;
learning, by using the plurality of pieces of first training data, the plurality of pieces of second training data, and the pseudo data, a classification model that classifies data into one of a pseudo class for classifying the pseudo data and the plurality of classification classed other than the pseudo class and that is constructed by a neural network;
classifying, by using the classification model, input data as a target for classification into one of the pseudo class and the plurality of classification classes; and
outputting information indicating that the input data classified into the pseudo class is data not belonging any of the plurality of classification classes,
wherein the classification method further comprises:
generating processed pseudo data with at least one of a plurality of pieces of training data and the generated pseudo data having been converted, the plurality of pieces of training data including the plurality of pieces of first training data and the plurality of pieces of second training data,
learning the classification model so as to classify the pseudo data and the processed pseudo data into the pseudo class, and
changing, according to number of times of learning, a ratio of a generation amount of the processed pseudo data to a total amount of data used in a learning of the classification model.