User guide

• 1. Introduction
  • 1.1. Introduction
  • 1.2. Mathematical formulation
  • 1.3. Challenge: lengths of time series
  • 1.4. Notations
• 2. Classification of raw time series
  • 2.1. KNeighborsClassifier
  • 2.2. SAXVSM
  • 2.3. BOSSVS
  • 2.4. LearningShapelets
  • 2.5. TimeSeriesForest
  • 2.6. Time Series Bag-of-Features
• 3. Extracting features from time series
  • 3.1. ShapeletTransform
  • 3.2. BagOfPatterns
  • 3.3. BOSS
  • 3.4. WEASEL
  • 3.5. ROCKET
• 4. Imaging time series
  • 4.1. Recurrence Plot
  • 4.2. Gramian Angular Field
  • 4.3. Markov Transition Field
• 5. Preprocessing utilities
  • 5.1. Imputing missing values
  • 5.2. Scaling
  • 5.3. Non-linear transformation
• 6. Decomposing time series
  • 6.1. Singular Spectrum Analysis
• 7. Approximating time series
  • 7.1. Piecewise Aggregate Approximation
  • 7.2. Symbolic Aggregate approXimation
  • 7.3. Discrete Fourier Transform
  • 7.4. Multiple Coefficient Binning
  • 7.5. Symbolic Fourier Approximation
• 8. Bag of words for time series
  • 8.1. Bag of words
  • 8.2. Word Extractor
• 9. Metrics for time series
  • 9.1. Classic Dynamic Time Warping
  • 9.2. Variants of Dynamic Time Warping
  • 9.3. Implementations
• 10. Multivariate time series
  • 10.1. Classification
  • 10.2. Transformation
  • 10.3. Image
• 11. Dataset loading utilities
  • 11.1. Simulated datasets
  • 11.2. Univariate time series: UCR repository
  • 11.3. Multivariate time series: UEA repository