Abstract:
Provided is a learning model generation system capable of preventing a decrease in prediction accuracy in a case where the trend of an actual value of a prediction target has changed. The learning model generation means 71 generates a learning model using, as learning data, time series data in which a value of each explanatory variable used in prediction of a prediction target is associated with an actual value of the prediction target. The prediction means 72 calculates a predicted value of the prediction target using the learning model once the value of each explanatory variable is given. The change point determination means 73 determines a change point which is a point in time when a trend of the actual value of the prediction target changed. The data correction means 74 corrects the time series data by adding a difference between the actual value and the predicted value of the prediction target at the change point and afterward to the actual value before the change point in the time series data when the change point is determined. The learning model generation means 71 regenerates the learning model using the time series data after the correction as the learning data once the time series data is corrected.
Abstract:
An information determination apparatus includes a first storage unit configured to store stream data pieces obtained in time sequence; a first determining unit configured to determine whether the number of stream data pieces stored in the first storage unit is at least equal to a predetermined value; and a second determining unit configured to determine, when the number of the stream data pieces stored in the first storage unit is equal to or greater than the predetermined value, whether an individual can be identified based on a dataset composed of a plurality of the stream data pieces stored in the first storage unit, and output the dataset used for the determination and the determination result.