| CPC G06N 3/0985 (2023.01) [G06N 3/126 (2013.01)] | 6 Claims |
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1. A hyperparameter tuning device including a processor, the hyperparameter tuning device comprising:
a learning processing unit operated by the processor and configured to train a learner, using a hyperparameter set of a first neural network as input of the learner, to cause the learner to output post-learning performance, the post-learning performance being performance of the first neural network in which the hyperparameter set is set responsive to the first neural network having been trained; and
a hyperparameter tuning unit operated by the processor and configured to tune the hyperparameter set of the first neural network by repeating a process, without training a plurality of the first neural networks in each of which a corresponding one of a plurality of hyperparameter sets is set, of generating a plurality of new hyperparameter sets on the basis of the plurality of hyperparameter sets, and inputting each of the plurality of new hyperparameter sets that have been generated into the learner that has been trained, to acquire the post-leaning performance of the plurality of the first neural networks in each of which a corresponding one of the plurality of new hyperparameter sets is set, wherein the plurality of new hyperparameter sets are generated based on the post-learning performance of a plurality of the first neural networks in each of which a corresponding one of a plurality of hyperparameter sets of the first neural network is set, the post-learning performance of the plurality of the first neural networks being acquired by inputting each of the plurality of hyperparameter sets to the learner that has been trained.
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