A learned model generating method includes: acquiring learning data; and generating a learned model for estimating a factor of an abnormality of a processing target substrate after processing using a processing fluid by performing machine learning of the learning data. The learning data includes a feature quantity and abnormality factor information. The abnormality factor information represents a factor of an abnormality of a learning target substrate after processing using the processing fluid. The feature quantity includes first feature quantity information representing a feature of a time transition of section data in time series data representing a physical quantity of an object used by a substrate processing device that processes the learning target substrate using the processing fluid. The first feature quantity information is represented using times.
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