Feature-based classification of time-series data

Authors:
Alex Nanopoulos;Rob Alcock;Yannis Manolopoulos
Affiliations:
Data Engineering Lab, Department of Informatics, Aristotle University, Thessaloniki 54006, GREECE;Data Engineering Lab, Department of Informatics, Aristotle University, Thessaloniki 54006, GREECE;Data Engineering Lab, Department of Informatics, Aristotle University, Thessaloniki 54006, GREECE
Venue:
Information processing and technology
Year:
2001

Citing 16
Cited 16

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Abstract

In this paper we propose the use of statistical features for time-series classification. The classification is performed with a multi-layer perceptron (MLP) neural network. The proposed method is examined in the context of Control Chart Pattern data, which are time series used in Statistical Process Control. Experimental results verify the efficiency of the feature-based classification method, compared to previous methods which classify time series based on the values of each time point. Moreover, the results show the robustness of the proposed method against noise and time-series length.