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Section Navigation

  • Plotting a time series
  • Approximating time series
    • Discrete Fourier Transform
    • Multiple Coefficient Binning
    • Piecewise Aggregate Approximation
    • Symbolic Aggregate approXimation
  • Bag-of-words transformation
    • Bag of Words
    • Word Extractor
  • Classification algorithms
    • Bag-of-SFA Symbols in Vector Space (BOSSVS)
    • Learning Time-Series Shapelets
    • Symbolic Aggregate approXimation in Vector Space Model (SAX-VSM)
    • Time Series Bag-of-Features
    • Time Series Forest
  • Clustering time series
    • Time Series Clustering with DTW and BOSS
  • Dataset utilities
    • Loading the GunPoint dataset
    • Making a Cylinder-Bell-Funnel dataset
  • Decomposing time series
    • Singular Spectrum Analysis
    • Trend-Seasonal decomposition with Singular Spectrum Analysis
  • Imaging time series
    • Data set of Gramian angular fields
    • Data set of Markov transition fields
    • Data set of recurrence plots
    • Single Gramian angular field
    • Single Markov transition field
    • Single recurrence plot
  • Metrics
    • Dynamic Time Warping
    • Itakura parallelogram
    • Sakoe-Chiba band
  • Multivariate time series
    • Joint Recurrence Plot
    • WEASEL+MUSE
  • Preprocessing tools
    • Imputer
    • Scalers
    • Transformers
  • Transformation algorithms
    • Bag of Patterns
    • Bag-of-SFA Symbols (BOSS)
    • RandOm Convolutional KErnel Transform (ROCKET)
    • Shapelet Transform
    • Word ExtrAction for time SEries cLassification (WEASEL)
  • Introductory examples
  • Clustering time series

Clustering time series#

Depending on a suitable metric, it is possible to cluster time series.

Time Series Clustering with DTW and BOSS

Time Series Clustering with DTW and BOSS
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