1. A method of classifying at least one test time series data set utilizing at least one training time series data set comprising the steps of: creating wavelet decomposed segments of the at least one training time series data set; discretizing the wavelet decomposed segments of the at least one training time series data set; determining one or more frequent patterns in the discretized wavelet decomposed segments of the at least one training time series data set; determining rules from the one or more frequent patterns in the discretized wavelet decomposed segments; and classifying one or more frequent patterns in the at least one test time series data set according to the rules.