Provided is an anomaly detection device capable of acquiring a degree of anomaly required for anomaly detection even when a feature pattern of time series data changes over time. The anomaly detection device of the present invention is a device that detects the degree of anomaly in the time series data. The anomaly detection device includes a first acquisition unit, a prediction unit, and an anomaly degree acquisition unit. The first acquisition unit acquires, from a first section that is a partial section of the time series data, a dynamic feature pattern of the first section. The prediction unit predicts data of a second section that is a partial section of the time series data later than the first section by using the feature pattern to obtain predicted second section data. The anomaly degree acquisition unit acquires the degree of anomaly based on a difference between the predicted second section data and actual data of the second section in the time series data.