Training data generation method and information processing apparatus

A training data generation method, comprising:

• acquiring, by a computer, a first feature from a machine learning model that estimates a first result of a target after a first period in response to an input of a first chronological state of the target in the first period, the first feature being a feature of the first chronological state;
• acquiring a second feature by inputting a second chronological state to the machine learning model, the second feature being a feature of the second chronological state in a second period including a period after the first result is determined;
• and
• generating, based on the first feature and the second feature, training data that takes the second chronological state as an explanatory variable and takes a second result as an objective variable, the second result being obtained by changing the determined first result.

An information processing apparatus, comprising:

• a memory;
• and
• a processor coupled to the memory and the processor configured to:
• acquire a first feature from a machine learning model that estimates a first result of a target after a first period in response to an input of a first chronological state of the target in the first period, the first feature being a feature of the first chronological state;
• acquire a second feature by inputting a second chronological state to the machine learning model, the second feature being a feature of the second chronological state in a second period including a period after the first result is determined;
• and
• generate, based on the first feature and the second feature, training data that takes the second chronological state as an explanatory variable and takes a second result as an objective variable, the second result being obtained by changing the determined first result.