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.
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