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JMotif implements in Java number of methods for timeseries data handling and analysis: * Z normalization of timeseries * Piecewise Aggregate Approximation (PAA) of timeseries * Symbolic Aggregate Approximation (SAX) of timeseries * iSAX (indexed SAX) in order to help one leverage the symbolic ... [More] representation of timeseries, it implements: * TFIDF statistics * Cosine similarity * Sequitur algorithm as well as their application for: * Motif (recurring patterns) detection with SAX * Discord (unique patterns) detection with SAX * Timeseries classification * Timeseries clustering [Less]