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The goal of early classification of time series is to predict the class value of a sequence early in time, when its full length is not yet available. This problem arises naturally in many contexts where the data is collected over time and the label predictions have to be made as soon as possible. In this work, a method based on probabilistic classifiers is(More)
In the past few years, clustering has become a popular task associated with time series. The choice of a suitable distance measure is crucial to the clustering process and, given the vast number of distance measures for time series available in the literature and their diverse characteristics, this selection is not straightforward. With the objective of(More)
In this document the generation process of the synthetic databases used in the work titled " Similarity Measure Selection for Clustering Time Series Databases " is explained in detail. By using this information and the code attached, the readers can easily generate the databases used in this study. Furthermore, the explanations and code enable the(More)
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