On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
Data Mining and Knowledge Discovery
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Proceedings of the VLDB Endowment
Time series shapelets: a new primitive for data mining
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Support vector machines of interval-based features for time series classification
Knowledge-Based Systems
Time series shapelets: a novel technique that allows accurate, interpretable and fast classification
Data Mining and Knowledge Discovery
Weighted dynamic time warping for time series classification
Pattern Recognition
A shapelet transform for time series classification
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Classification of time series by shapelet transformation
Data Mining and Knowledge Discovery
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Classification is a very broad and prevalent topic of research within data mining. Whilst heavily related, time series classification (TSC) offers a more specific challenge. One of the most promising approaches proposed for TSC is time series shapelets. In this paper, we assess the current quality measure for shapelet extraction and introduce two statistical tests for shapelet finding. We show that when compared to information gain, these two quality measures can speed up shapelet extraction whilst still producing classifiers that are as accurate as the original.