1. A learning apparatus comprising: location acquiring means for acquiring time series data on locations of a user; time acquiring means for acquiring time series data on times; learning means for learning an activity model indicating an activity state of the user as a probabilistic state transition model, using the respective acquired time series data on the locations and the times as an input; additional information acquiring means for acquiring time series data on additional information of one or more types other than the locations of the user and the times; state series generating means for generating time series data on state nodes from the time series data on the locations and the times by inputting the acquired time series data on the locations and the times in the activity model of the user learned by the learning means and outputting the time series data on the state nodes of the activity model of the user; selecting means for correspondingly storing the time series data on the additional information acquired by the additional information acquiring means and the time series data on the state nodes generated by the state series generating means, and for selecting only the time series data on the state nodes corresponding to the additional information at a current time point acquired by the additional information acquiring means from among the stored time series data in a case where the activity model of the user at the current time point is predicted using the activity model of the user learned by the learning means; and re-calculating means for re-calculating a parameter for the activity model of the user by a statistical process, using the time series data on the state nodes selected by the selecting means.