Library of multivariate time series
Description
A database of many different types of multivariate time series, each with between 5-25 processes and between 100-2500 observations.
The database contains a serialized Python dictionary of 1053 datasets, where the key for the dictionary is the dataset name, and each value is another dictionary of:data (an MxT numpy array of processes-by-observations) and labels (a list of descriptive labels for the dataset).