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

Probabilistic forecasting

Hierarchical, global, and panel forecasting

Forecasting with aeon and scikit-learn

Window splitters for forecasting

Classification#

Overview of Time Series Classification (TSC)

Convolution based TSC

Deep learning based TSC

Dictionary based TSC

Distance based TSC

Feature based TSC

Hybrid TSC

Interval based TSC

Shapelet based TSC

Early TSC

Regression#

Overview of Time Series Regression (TSR)

Clustering#

Overview of Time Series Clustering (TSCL)

Partitional TSCL

Transformation#

Overview of Transformations

TSFresh transform

Catch22 transform

Rocket transform

MiniRocket transform

SAST transform

Interpolation

Signature method

Theta transform

Segmentation#

Intro to segmentation

ClaSP segmentation

Hidalgo segmentation

Distances#

Distance functions

Using aeon distances with scikit-learn

Data Formatting and Loading#

Data in aeon

Data structures and containers used in aeon

Conversions between data structures

How series are stored in file and loaded into memory

Example data sets

Loading data from the web

Benchmarking#

Benchmarking algorithms

Benchmarking forecasting algorithms

Benchmarking extrinsic regression algorithms

Compare regression algorithms on a single dataset

Getting estimator reference results

Getting published bakeoff results

Base#

aeon base classes

Series base classes

Utils#

Preprocessing collections of time series