tslearn.barycenters¶
The tslearn.barycenters
module gathers algorithms for time series
barycenter computation.
A barycenter (or Fréchet mean) is a time series \(b\) which minimizes the sum of squared distances to the time series of a given data set \(x\):
\[\min \sum_i d( b, x_i )^2\]
Only the methods dtw_barycenter_averaging()
and
softdtw_barycenter()
can operate on variable-length time-series
(see here).
See the barycenter examples for an overview.
Functions
euclidean_barycenter (X[, weights]) |
Standard Euclidean barycenter computed from a set of time series. |
dtw_barycenter_averaging (X[, …]) |
DTW Barycenter Averaging (DBA) method estimated through Expectation-Maximization algorithm. |
dtw_barycenter_averaging_subgradient (X[, …]) |
DTW Barycenter Averaging (DBA) method estimated through subgradient descent algorithm. |
softdtw_barycenter (X[, gamma, weights, …]) |
Compute barycenter (time series averaging) under the soft-DTW [1] geometry. |