Signal selection device, learning device, and signal selection method and program

A learning method for selecting, from a plurality of candidate signals, a training signal for learning a model usable for data analysis and learning the model based on the training signal, the method comprising:

• calculating, by a feature calculator, a feature using the plurality of candidate signals;
• selecting, by a selector, the training signal from the plurality of candidate signals based on a degree of relevance between the feature and training labels being status values corresponding to results of analysis performed using the model;
• repeating, by a learner, changing a value of each of a plurality of the training signals to generate a new model;
• and
• calculating and outputting, by a contribution outputter, a degree of contribution based on a comparison between the training labels and labels assigned to the plurality of training signals in accordance with the new model generated through the repeated changing, the degree of contribution indicating a degree of contribution of the plurality of training signals selected in the selecting to label assignment performed using the model.

A non-transitory computer-readable recording medium storing a program, the program causing a computer to select, from a plurality of candidate signals, a training signal for learning a model usable for data analysis and learning the model based on the training signal, the program causing the computer to perform operations comprising:

• calculating a feature using the plurality of candidate signals;
• selecting the training signal from the plurality of candidate signals based on a degree of relevance between the feature and training labels being status values corresponding to results of analysis performed using the model
• repeating changing a value of each of a plurality of the training signals to generate a new model;
• and
• calculating and outputting a degree of contribution based on a comparison between the training labels and labels assigned to the plurality of training signals in accordance with the new model generated through the repeated changing, the degree of contribution indicating a degree of contribution of the selected plurality of training signals to label assignment performed using the model.