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tslearn 0.8.1 documentation - Home tslearn 0.8.1 documentation - Home
  • Quick-start guide
  • User Guide
  • API Reference
  • Gallery of examples
  • Citing tslearn
  • GitHub
  • Quick-start guide
  • User Guide
  • API Reference
  • Gallery of examples
  • Citing tslearn
  • GitHub

Section Navigation

  • Metrics
    • Canonical Time Warping
    • Dynamic Time Warping
    • DTW computation with a custom distance metric
    • Frechet
    • LB_Keogh
    • Longest Common Subsequence
    • Longest Common Subsequence with a custom distance metric
    • sDTW multi path matching
    • Soft Dynamic Time Warping
  • Nearest Neighbors
    • k-NN search
    • Hyper-parameter tuning of a pipeline with KNeighbors time series classifier
    • Nearest neighbors
    • 1-NN with SAX + MINDIST
  • Clustering and Barycenters
    • DBSCAN
    • Soft-DTW weighted barycenters
    • Barycenters
    • Kernel k-means
    • k-means
    • KShape
  • Classification
    • Early Classification
    • Learning Shapelets: decision boundaries in 2D distance space
    • Aligning discovered shapelets with timeseries
    • Learning Shapelets
    • SVM and GAK
  • Automatic differentiation
    • Soft-DTW loss for PyTorch neural network
  • Miscellaneous
    • Distance and Matrix Profiles
    • Matrix Profile
    • PAA and SAX features
    • Model Persistence
  • Gallery of examples
  • Metrics

Metrics#

Canonical Time Warping

Canonical Time Warping

Dynamic Time Warping

Dynamic Time Warping

DTW computation with a custom distance metric

DTW computation with a custom distance metric

Frechet

Frechet

LB_Keogh

LB_Keogh

Longest Common Subsequence

Longest Common Subsequence

Longest Common Subsequence with a custom distance metric

Longest Common Subsequence with a custom distance metric

sDTW multi path matching

sDTW multi path matching

Soft Dynamic Time Warping

Soft Dynamic Time Warping

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Gallery of examples

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Canonical Time Warping

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