Learning data processing device, learning data processing method and non-transitory computer-readable medium

A learning data processing method of generating learning data used in a learning device that generates a learning model on the basis of time-series data including at least one kind of measured value, the method including at least one of:

• a first step in which a statistical value of measured values included in one or multiple predetermined periods of the time-series data and at least one of an outlier determination upper limit value or an outlier determination lower limit value based on the statistical value are calculated, and, of measured values included in the predetermined period, measured values that are at least one of those greater than or equal to the outlier determination upper limit value or those less than or equal to the outlier determination lower limit value are removed from the time-series data;
• or
• a second step in which, of measured values included in the time-series data, measured values satisfying a predetermined condition are removed from the time-series data.

A non-transitory computer-readable medium configured to store a learning data processing program that causes a processor to generate leaning data used in a leaning device that generates a learning model on the basis of time-series data including at least one kind of measured value, wherein

• the learning data processing program causes the processor to execute at least one of a first step in which a statistical value of measured values included in one or multiple predetermined periods of the time-series data and at least one of an outlier determination upper limit value or an outlier determination lower limit value based on the statistical value are calculated, and, of measured values included in the one or multiple predetermined periods, measured values that are at least one of those greater than or equal to the outlier determination upper limit value or those less than or equal to the outlier determination lower limit value are removed from the time-series data, or a second step in which, of measured values included in the time-series data, measured values satisfying a predetermined condition are removed from the time-series data.