Abstract: A learning apparatus according to an embodiment includes: input means for inputting training data for learning a classifier and a causal graph representing causal relationships between variables included in the training data; and learning means for learning the classifier by solving a constrained optimization problem in which a mean of causal effects between predetermined variables is within a predetermined range and a variance of the causal effects is equal to or smaller than a predetermined value, using the training data and the causal graph input by the input means.

Abstract: A technique for estimating a causal relation, which can solve problems of a conventional technique and which does not require preliminary setting of a regression model is disclosed. An embodiment of the present invention relates to a causal relation learning device including: a feature value calculation unit that receives a correct label of three or more classification labels related to a causal relation of time-series data and time-series data corresponding to the correct label and calculates a feature value of the time-series data; and a classifier learning unit that learns a classifier using a set of the feature value and the correct label so that an output of the classifier with respect to the feature value is a largest value of an output value of the correct label.