Abstract: A data generation method for generating data for domain generalization in machine learning includes performing, with a computer, augmentation using training data as raw data usable to train a machine learning model, and extracting, with the computer, a dataset including the raw data and data generated through the augmentation as a dataset for the domain generalization.

Abstract: The present invention reduces costs relating to generation of a model, and suppresses a decrease in the estimating accuracy of the generated model. A quality prediction system of one aspect of the present invention acquires first learning data collected in first manufacturing equipment, acquires second learning data collected in second manufacturing equipment, and in order to implement transfer learning, converts the acquired first learning data to match the second learning data, uses the converted first learning data and the second learning data to implement machine learning of a quality prediction model, uses a trained quality prediction model to specify an adjustment amount for each adjustment item of the second manufacturing equipment so that a quality index predicted for a second product satisfies a quality standard, and outputs the specified adjustment amount of each adjustment item of the second manufacturing equipment.