# 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.