This is the Meat dataset from UCR Archive modified for Salient discovery. The original data is mixed with Random Walks and the algorithm must pick only the originals.
mp_meat_data
original
is the original dataset with 60+60 observations mixed with 120 random walks:
240 time series with length of 448 each.
label of each time series, -666
means a random walk.
size of sliding window.
sub
is the original dataset embedded in random walks:
One time series with length of 107520.
label of each original data.
starting point where the original data was placed.
size of sliding window.
http://www.cs.ucr.edu/~eamonn/time_series_data/
Yeh CCM, Van Herle H, Keogh E. Matrix profile III: The matrix profile allows visualization of salient subsequences in massive time series. Proc - IEEE Int Conf Data Mining, ICDM. 2017;579-88.
Hu B, Rakthanmanon T, Hao Y, Evans S, Lonardi S, Keogh E. Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL. In: 2011 IEEE 11th International Conference on Data Mining. IEEE; 2011. p. 1086-91.