Julia implementation of unsupervised learning methods for time series datasets. It provides functionality for clustering and aggregating, detecting motifs, and quantifying similarity between time series datasets.
In general a great inclusion of the wide range of problems that it can tackle!
Reading it I had difficulty to understand that the variable names are the attributes and we don't have a > third variable name that we load. I thought of adding 'which we call'. What do you think @holgerteichgraeber ?
I almost overlooked the comment in the commit message, a PR seems to help better with tracking.
I almost overlooked the comment in the commit message, a PR seems to help better with tracking.