EthanolLevel UCR Archive Dataset

This dataset is part of the UCR Archive maintained by University of Southampton researchers. Please cite a relevant or the latest full archive release if you use the datasets. See http://www.timeseriesclassification.com/.

This dataset is part of the project with Scotch Whisky Research Institute into detecting forged spirits in a non-intrusive manner. One way of detecting forgery without sampling the wine is through inspecting ethanol level by spectrograph.  The dataset covers 20 different bottle types and four levels of alcohol: 35%, 38%, 40% and 45%. Each series is a spectrograph of 1751 observations.  This dataset is an example of when it is wrong to merge and resample, because the train/test split are constructed so that the same bottle type is never in both train and test sets.  There are 4 classes.  - Class 1: E35 - Class 2: E38 - Class 3: E40 - Class 4: E45  For more information about this dataset, see [1,2].  

[1] Lines, Jason, Sarah Taylor, and Anthony Bagnall. "Hive-cote: The hierarchical vote collective of transformation-based ensembles for time series classification." Data Mining (ICDM), 2016 IEEE 16th International Conference on. IEEE, 2016.

[2] J. Large, E. K. Kemsley, N.Wellner, I. Goodall, and A. Bagnall, Detecting forged alcohol non-invasively through vibrational spectroscopy and machine learning," in Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2018.

Donator: A. Bagnall