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tslearn 0.9.0.dev0 documentation - Home tslearn 0.9.0.dev0 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
  • Gallery of examples

Gallery of examples#

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

Nearest Neighbors#

k-NN search

k-NN search

Hyper-parameter tuning of a pipeline with KNeighbors time series classifier

Hyper-parameter tuning of a pipeline with KNeighbors time series classifier

Nearest neighbors

Nearest neighbors

1-NN with SAX + MINDIST

1-NN with SAX + MINDIST

Clustering and Barycenters#

DBSCAN

DBSCAN

Soft-DTW weighted barycenters

Soft-DTW weighted barycenters

Barycenters

Barycenters

Kernel k-means

Kernel k-means

k-means

k-means

KShape

KShape

Classification#

Early Classification

Early Classification

Learning Shapelets: decision boundaries in 2D distance space

Learning Shapelets: decision boundaries in 2D distance space

Aligning discovered shapelets with timeseries

Aligning discovered shapelets with timeseries

Learning Shapelets

Learning Shapelets

SVM and GAK

SVM and GAK

Automatic differentiation#

Soft-DTW loss for PyTorch neural network

Soft-DTW loss for PyTorch neural network

Miscellaneous#

Distance and Matrix Profiles

Distance and Matrix Profiles

Matrix Profile

Matrix Profile

PAA and SAX features

PAA and SAX features

Model Persistence

Model Persistence

Download all examples in Python source code: auto_examples_python.zip

Download all examples in Jupyter notebooks: auto_examples_jupyter.zip

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