I have a data set in which the samples are multivariate (about 30 variable/features) time series. These samples refer to two classes. I would like to select the variables more relevant to discriminate between the classes and also to remove redundant variables. I am thinking about a filter method for feature selection (I am not interested on a specific predictor), but I have never worked with time series. I know Fisher score and AUC method, but I don't know how I could apply to these data. Anyone could provide me with some help?