Regression#
The aeon.regression
module contains algorithms and composition tools for time series regression.
All regressors in aeon``can be listed using the ``aeon.registry.all_estimators
utility,
using estimator_types="regressor"
, optionally filtered by tags.
Valid tags can be listed using aeon.registry.all_tags
.
Convolution-based#
|
Regressor wrapped for the Rocket transformer using RidgeCV regressor. |
|
Hydra Regressor. |
|
MultiRocket-Hydra Regressor. |
Deep learning#
|
Time Series Convolutional Neural Network (CNN). |
|
Fully Convolutional Network (FCN). |
|
Time series attentional prototype network (TapNet). |
|
InceptionTime ensemble regressor. |
|
Single Inception regressor. |
|
Residual Neural Network. |
Distance-based#
|
K-Nearest Neighbour Time Series Regressor. |
Dummy#
|
DummyRegressor makes predictions that ignore the input features. |
Feature-based#
|
Canonical Time-series Characteristics (catch22) regressor. |
|
Fresh Pipeline with RotatIoN forest Regressor. |
|
Summary statistic regressor. |
|
Time Series Feature Extraction based on Scalable Hypothesis Tests regressor. |
Hybrid#
Interval-based#
|
Time series forest (TSF) regressor. |
Shapelet-based#
|
A random dilated shapelet transform (RDST) regressor. |
sklearn#
|
A Rotation Forest (RotF) vector regressor. |
Base#
Abstract base class for time series regressors. |
|
Abstract base class for deep learning time series regression. |