tslearn 0.5.3.2
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    Gallery of examples¶

    Metrics¶

    Longest Common Subsequence

    Longest Common Subsequence

    Longest Common Subsequence
    LB_Keogh

    LB_Keogh

    LB_Keogh
    Canonical Time Warping

    Canonical Time Warping

    Canonical Time Warping
    sDTW multi path matching

    sDTW multi path matching

    sDTW multi path matching
    Longest Commom Subsequence with a custom distance metric

    Longest Commom Subsequence with a custom distance metric

    Longest Commom Subsequence with a custom distance metric
    Dynamic Time Warping

    Dynamic Time Warping

    Dynamic Time Warping
    Soft Dynamic Time Warping

    Soft Dynamic Time Warping

    Soft Dynamic Time Warping
    DTW computation with a custom distance metric

    DTW computation with a custom distance metric

    DTW computation with a custom distance metric

    Nearest Neighbors¶

    k-NN search

    k-NN search

    k-NN search
    Nearest neighbors

    Nearest neighbors

    Nearest neighbors
    Hyper-parameter tuning of a Pipeline with KNeighborsTimeSeriesClassifier

    Hyper-parameter tuning of a Pipeline with KNeighborsTimeSeriesClassifier

    Hyper-parameter tuning of a Pipeline with KNeighborsTimeSeriesClassifier
    1-NN with SAX + MINDIST

    1-NN with SAX + MINDIST

    1-NN with SAX + MINDIST

    Clustering and Barycenters¶

    KShape

    KShape

    KShape
    Kernel k-means

    Kernel k-means

    Kernel k-means
    Barycenters

    Barycenters

    Barycenters
    Soft-DTW weighted barycenters

    Soft-DTW weighted barycenters

    Soft-DTW weighted barycenters
    k-means

    k-means

    k-means

    Classification¶

    SVM and GAK

    SVM and GAK

    SVM and GAK
    Learning Shapelets

    Learning Shapelets

    Learning Shapelets
    Early Classification

    Early Classification

    Early Classification
    Aligning discovered shapelets with timeseries

    Aligning discovered shapelets with timeseries

    Aligning discovered shapelets with timeseries
    Learning Shapelets: decision boundaries in 2D distance space

    Learning Shapelets: decision boundaries in 2D distance space

    Learning Shapelets: decision boundaries in 2D distance space

    Miscellaneous¶

    Model Persistence

    Model Persistence

    Model Persistence
    PAA and SAX features

    PAA and SAX features

    PAA and SAX features
    Matrix Profile

    Matrix Profile

    Matrix Profile
    Distance and Matrix Profiles

    Distance and Matrix Profiles

    Distance and Matrix Profiles

    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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    © Copyright 2017, Romain Tavenard.
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