Abstract: A method of reducing training data via a system having an encoder, wherein at least a portion of the training data forms a temporal sequence and is combined into a first set of training data, and the encoder maps input data to prototype feature vectors of a set of prototype feature vectors. A first input datum is received from the first set of training data, and propagated by the encoder. The input datum is assigned one or more feature vectors by the encoder, and depending on the assigned feature vectors, a defined set of prototype feature vectors is determined and assigned to the first input datum. An aggregated vector is created for the first input datum. A second aggregated vector is created for the second input datum and the first and second aggregated vectors are compared and a measure of similarity for the aggregated vectors is determined.