Measuring similarity of univariate time seriesKljun, Maša (Avtor) Štrumbelj, Erik (Mentor) time seriessimilarity measuresclassification of similarity measuresclusteringIn this thesis we review 12 time series similarity measures and 3 classifications of these measures into groups. We view similarity measures in terms of time complexity, support of time series of different lengths, and normalization. With empirical evaluation we check measures' invariances to warping and scaling, their clustering performance, and how similar they are. We find out that although several measures perform well on average no measure performs well in all cases. We see that the Piccolo distance is invariant to warping and scaling, and that it stands out with its clustering performance and linear time complexity. We also see that compression-based measures perform poorly on average.20202020-09-07 15:50:05Diplomsko delo/naloga119310sl