Time series regression#
The sktime.regression
module contains algorithms and composition tools for time series regression.
All regressors in sktime
can be listed using the sktime.registry.all_estimators
utility,
using estimator_types="regressor"
, optionally filtered by tags.
Valid tags can be listed using sktime.registry.all_tags
.
Composition#
Time-Series Forest Regressor. |
Deep learning#
|
Time Series Convolutional Neural Network (CNN), as described in [1]. |
|
Fully Connected Neural Network (FCN), as described in [Rea5a1664c466-1]. |
|
Multi Channel Deep Convolutional Neural Regressor, adopted from [R244bb0d4e2ae-1]. |
|
Multi Layer Perceptron Network (MLP), as described in [R15a0eceb2106-1]. |
|
Simple recurrent neural network. |
|
Residual Neural Network Regressor adopted from [1]. |
|
Time series attentional prototype network (TapNet), as described in [1]. |
Distance-based#
|
KNN Time Series Regressor. |
Dummy#
|
DummyRegressor makes predictions that ignore the input features. |
Interval-based#
|
Time series forest regressor. |
Kernel-based#
|
Regressor wrapped for the Rocket transformer using RidgeCV regressor. |
Base#
Abstract base class for time series regressors. |
|
Abstract base class for deep learning time series regression. |