An anomaly detection apparatus having a function of an autoencoder that includes an input layer, hidden layers, and an output layer, and that learns parameters such that data of the input layer is reproduced in the output layer, the anomaly detection apparatus including: input means that input normal data of a plurality of types; learning means that learn parameters such that normal data of the input layer is reproduced in the output layer by learning a feature across data types using data of a dimension which is smaller than a dimension of the normal data; and anomaly degree calculation means that input test data to the autoencoder using the parameters learned by the learning means, and calculate anomaly degree of the test data based on output data of the autoencoder and the test data.