Displaying iterative learning process and sample error to efficiently eliminate noisy sample data

A learning method comprising:

• acquiring a plurality of learning samples to be learned and a plurality of target labels associated with the respective learning samples;
• iteratively cause learning by a learning model which receives an input of a learning sample, among the plurality of learning sample, and outputs output data and a learning error, the learning error representing an error between the output data corresponding to the inputted learning sample and a target label, among the plurality of target labels;
• and
• displaying, based on a learning progress regarding the iterative learning of the learning model and a plurality of learning errors, a layout image in which at least some of the learning samples are arranged for each point in the learning progress and according to the learning errors.

A non-transitory computer-readable storage medium storing a program for causing a computer to execute processing comprising:

• acquiring a plurality of learning samples to be learned and a plurality of target labels associated with the respective learning samples;
• iteratively cause learning by a learning model which receives an input of a learning sample, among the plurality of learning sample, and outputs output data and a learning error, the learning error representing an error between the output data corresponding to the inputted learning sample and a target label, among the plurality of target labels;
• and
• displaying, based on a learning progress regarding the iterative learning of the learning model and a plurality of learning errors, a layout image in which at least some of the learning samples are arranged for each point in the learning progress and according to the learning errors.