Estimation method and apparatus

An estimation apparatus comprising:

• a memory configured to store measured data in which a first data size is associated with a prediction performance of a model generated by using training data of the first data size;
• and
• a processor configured to execute a process including:
• calculating, based on the measured data, a first parameter value which defines a first prediction performance curve that indicates a relationship between a data size and a prediction performance,
• sampling a prediction performance within a predetermined range from the first prediction performance curve a plurality of times for each of different data sizes, to generate a plurality of sample point sequences, each of which is a sequence of combinations of a data size and a prediction performance,
• calculating a plurality of second parameter values which defines a plurality of second prediction performance curves that represents the plurality of sample point sequences and determining a plurality of weights associated with the plurality of second prediction performance curves by using the plurality of second parameter values and the measured data, and
• generating variance information which indicates variation of a prediction performance of a second data size estimated from the first prediction performance curve by using the plurality of second prediction performance curves and the plurality of weights.

A non-transitory computer-readable storage medium storing a computer program that causes a computer to execute a process comprising:

• calculating, based on measured data in which a first data size is associated with a prediction performance of a model generated by using training data of the first data size, a first parameter value which defines a first prediction performance curve that indicates a relationship between a data size and a prediction performance,
• sampling a prediction performance within a predetermined range from the first prediction performance curve a plurality of times for each of different data sizes, to generate a plurality of sample point sequences, each of which is a sequence of combinations of a data size and a prediction performance,
• calculating a plurality of second parameter values which defines a plurality of second prediction performance curves that represents the plurality of sample point sequences and determining a plurality of weights associated with the plurality of second prediction performance curves by using the plurality of second parameter values and the measured data, and
• generating variance information which indicates variation of a prediction performance of a second data size estimated from the first prediction performance curve by using the plurality of second prediction performance curves and the plurality of weights.