Importance

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Abstract

A machine learning management apparatus calculates, for each of a plurality of second models that are generated by model searches by a plurality of algorithms using a plurality of sets of second training data and based on prediction performance of first models, an index value used to determine whether to generate each second model. The machine learning management apparatus then sets the number of second models that are generated using a set of second training data and have an index value at least equal to a threshold as the priority for caching that second training data. The machine learning management apparatus then decides, when a model search has been executed using second training data, whether to cache the second training data based on the priority and stores the second training data in a memory when the decision to cache the data is taken.

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First Claim