Method of performing classification processing using machine learning model, information processing device, and computer program

An information processing device configured to perform classification processing on classification target data using a machine learning model including a vector neural network including a plurality of vector neuron layers, the information processing device comprising:

• a memory configured to store the machine learning model;
• and
• one or more processors configured to execute computation using the machine learning model, wherein
• the one or more processors perform:
• (a) processing of preparing N machine learning models, each of the N machine learning models being configured to classify input data into any one of a plurality of classes, each of the N machine learning models being also configured to include at least one class differing from other machine learning models of the N machine learning models, where N is an integer equal to or more than 2;
• (b) processing of, when a plurality of pieces of training data are input into the N machine learning models, preparing a known feature vector group obtained from output of at least one specific layer of the plurality of vector neuron layers;
• and
• (c) processing of computing, using a selected machine learning model selected from the N machine learning models a similarity, for each class, between the known feature vector group and a feature vector obtained from output of the specific layer when the classification target data is input into the selected machine learning model, and determining a class for the classification target data using the similarity.

A non-transitory computer-readable storage medium storing a computer program, the computer program being configured to cause one or more processors to perform classification processing on classification target data using a machine learning model including a vector neural network including a plurality of vector neuron layers, the computer program being configured to cause the one or more processors to perform:

• (a) processing of preparing N machine learning models, each of the N machine learning models being configured to classify input data into any one of a plurality of classes, each of the N machine learning models being also configured to include at least one class differing from other machine learning models of the N machine learning models, where N is an integer equal to or more than 2;
• (b) processing of, when a plurality of pieces of training data are input into the N machine learning models, preparing a known feature vector group obtained from output of at least one specific layer of the plurality of vector neuron layers;
• and
• (c) processing of computing, using a selected machine learning model selected from the N machine learning models, a similarity, for each class, between the known feature vector group and a feature vector obtained from output of the specific layer when the classification target data is input into the selected machine learning model, and determining a class for the classification target data using the similarity.