Examples

This webpage contains the notebook examples for the aeon library. The examples are organised into categories based on module and functionality. The examples are designed to provide a comprehensive overview of a module, functionality or a specific algorithm.

Forecasting

Overview of forecasting

Forecasting with aeon

Probabilistic forecasting

/examples/forecasting/forecasting_proba.ipynb

Hierarchical, global, and panel forecasting

Hierarchical, Global, and Panel Forecasting with aeon

Forecasting with aeon and scikit-learn

Forecasting, supervised regression, and pitfalls in confusing the two

Window splitters for forecasting

Window Splitters in aeon

Classification

Overview of Time Series Classification (TSC)

Time Series Classification with aeon

Convolution based TSC

Convolution based time series classification in aeon

Deep learning based TSC

Deep learning based time series classification in aeon

Dictionary based TSC

Dictionary based time series classification in aeon

Distance based TSC

Distance based time series classification in aeon

Feature based TSC

Feature based time series classification in aeon

Hybrid TSC

Hybrid time series classification in aeon

Interval based TSC

Interval based time series classification in aeon

Shapelet based TSC

Shapelet based time series machine learning

Early TSC

Early time series classification with aeon

Regression

Overview of Time Series Regression (TSR)

Time Series Extrinsic Regression (TSER) with aeon

Clustering

Overview of Time Series Clustering (TSCL)

Time series clustering

Partitional TSCL

Partition based time series clustering in aeon

Transformation

Overview of Transformations

Transforming time series with aeon

TSFresh transform

Feature extraction with tsfresh transformer

Catch22 transform

The Canonical Time-series Characteristics (catch22) transform

Rocket transform

Demo of ROCKET transform

MiniRocket transform

MiniRocket

SAST transform

Demo of SAST transform

Interpolation

Time series interpolating with aeon

Signature method

The Signature Method with aeon

Theta transform

Theta Lines transformer

Segmentation

Intro to segmentation

Time Series Segmentation

ClaSP segmentation

Time Series Segmentation with aeon and ClaSP

Hidalgo segmentation

Hidalgo segmentation

Distances

Distance functions

Distance Functions in aeon

Using aeon distances with scikit-learn

Using aeon distances with scikit learn

Data Formatting and Loading

Data in aeon

Loading/storing/converting data in aeon

Data structures and containers used in aeon

Data structures and containers to use for aeon estimators

Conversions between data structures

Data conversions in aeon

How series are stored in file and loaded into memory

Loading data into aeon

Example data sets

Provided datasets

Loading data from the web

Downloading and loading benchmarking datasets

Unequal length series

Loading data with unequal length series or missing values

Benchmarking

Benchmarking algorithms

Benchmarking - comparing estimator performance

Benchmarking forecasting algorithms

Instantiate an instance of a benchmark class

Benchmarking extrinsic regression algorithms

Benchmarking time series regression models

Compare regression algorithms on a single dataset

Benchmarking: comparing estimators on a specific datasets

Getting estimator reference results

Benchmarking: retrieving and comparing against reference results

Getting published bakeoff results

Benchmarking: retrieving and comparing against published results

Base

aeon base classes

Overview of the base class structure

Series base classes

BaseSeriesEstimator

Utils

Preprocessing collections of time series

Preprocessing data prior to machine learning