TRAINING DEVICE, TRAINING METHOD, AND TRAINING PROGRAM

1 . A learning device comprising:

processing circuitry configured to:

acquire a plurality of pieces of communication data for learning;

extract feature amounts of the communication data;

train a generative model with the feature amounts of the communication data;

extract first representative points of the feature amounts of the communication data using kernel herding; and

output the first representative points extracted.

2 . The learning device according to claim 1 , wherein the processing circuitry is further configured to:

generate a plurality of pieces of data from the generative model,

extract second representative points of the generated data using kernel herding, and

output the second representative points extracted.

3 . The learning device according to claim 2 , wherein a difference between the first representative points extracted and the second representative points extracted is used in an evaluation of progress of the generative model.

4 . A learning method executed by a learning device, the learning method comprising:

acquiring a plurality of pieces of communication data for learning;

extracting feature amounts of the communication data;

training a generative model with the feature amounts of the communication data;

extracting representative points of the feature amounts of the communication data using kernel herding; and

outputting the representative points.

5 . A non-transitory computer-readable recording medium storing therein a learning program that causes a computer to execute a process comprising:

acquiring a plurality of pieces of communication data for learning;

extracting feature amounts of the communication data;

training a generative model with the feature amounts of the communication data;

extracting representative points of the feature amounts of the communication data using kernel herding; and

outputting the representative points.