Pattern Graphs: Combining Multivariate Time Series and Labelled Interval Sequences for Classification
作者： Sebastian Peter , Frank Höppner , Michael R. Berthold
DOI: 10.1007/978-3-319-02621-3_1
关键词:
摘要: Classifying multivariate time series is often dealt with by transforming the numeric into labelled intervals, because many pattern representations exist to deal intervals. Finding right preprocessing not only consuming but also critical for success of learning algorithms. In this paper we show how graphs, a powerful language temporal classification rules, can be extended in order handle intervals combination raw series. We thereby reduce dependence on quality and at same increase performance. These benefits are demonstrated experimentally 10 different data sets.
uni-konstanz.de
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sci-hub.st 参考文章(13)
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