Time Series Clustering Along with Optimizations for the Dynamic
Time Warping Distance
Description
Time series clustering along with optimized techniques related
to the Dynamic Time Warping distance and its corresponding lower bounds.
Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole
clustering are available. Functionality can be easily extended with
custom distance measures and centroid definitions. Implementations of
DTW barycenter averaging, a distance based on global alignment kernels,
and the soft-DTW distance and centroid routines are also provided.
All included distance functions have custom loops optimized for the
calculation of cross-distance matrices, including parallelization support.
Several cluster validity indices are included.