Abstract
Investigating time series with respect to statistical analysis and forecasting is a well established area. In this paper we study the problem of matching time series. This paper addresses the problem how to choose the attributes describing the time points with respect to certain matching problem. Furthemore, this paper introduce an algorithm, computing the domain error of a classifier of the model, which can be used as an evaluation function of the classifier with respect to the matching problem. The exeprimental results, presented in this paper, illustrate the usefulness of the evaluation.
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Dugarjapov, A., Lausen, G. (2003). Mining Sets of Time Series: Description of Time Points. In: Schwaiger, M., Opitz, O. (eds) Exploratory Data Analysis in Empirical Research. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55721-7_5
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DOI: https://doi.org/10.1007/978-3-642-55721-7_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44183-0
Online ISBN: 978-3-642-55721-7
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