Time series regression

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 are listed in the regressor tags API reference, and can be listed using sktime.registry.all_tags.

A full table with tag based search is also available on the Estimator Search Page (select “regresser” in the “Estimator type” dropdown).

Composition

RegressorPipeline(regressor, transformers)	Pipeline of transformers and a regressor.
SklearnRegressorPipeline(regressor, transformers)	Pipeline of transformers and a regressor.
MultiplexRegressor(regressors[, ...])	MultiplexRegressor for selecting among different models.

Model selection and tuning

TSRGridSearchCV(estimator, param_grid[, ...])

Exhaustive search over specified parameter values for an estimator.

Ensembles

ComposableTimeSeriesForestRegressor([...])

Time-Series Forest Regressor.

Deep learning

cnn.CNNRegressor([n_epochs, batch_size, ...])	Time Series Convolutional Neural Network (CNN), as described in [1].
cnn.CNNRegressorTorch([num_epochs, ...])	Time Convolutional Neural Network (CNN) in PyTorch, as described in [1].
cntc.CNTCRegressor([n_epochs, batch_size, ...])	Contextual Time-series Neural Regressor (CNTC), as described in [1].
convtran.ConvTranRegressorTorch([net_type, ...])	ConvTran regressor in PyTorch.
fcn.FCNRegressor([n_epochs, batch_size, ...])	Fully Connected Neural Network (FCN), as described in [Ra149bfda32b6-1].
inceptiontime.InceptionTimeRegressor([...])	InceptionTime Deep Learning Regressor.
inceptiontime.InceptionTimeRegressorTorch([...])	InceptionTime Deep Learning Regressor in PyTorch.
lstmfcn.LSTMFCNRegressor([n_epochs, ...])	Implementation of LSTMFCNRegressor from Karim et al (2019) [1].
lstmfcn.LSTMFCNRegressorTorch([...])	LSTM-FCN regressor for time series regression in PyTorch.
macnn.MACNNRegressor([n_epochs, batch_size, ...])	Multi-Scale Attention Convolutional Neural Regressor, as described in [Rb74eb9799e5d-1].
mcdcnn.MCDCNNRegressor([n_epochs, ...])	Multi Channel Deep Convolutional Neural Regressor, adopted from [R1d70ab7b779e-1].
mcdcnn.MCDCNNRegressorTorch([n_epochs, ...])	Multi Channel Deep Convolutional Neural Regressor in PyTorch, adopted from [R48f9c500d89f-1].
mlp.MLPRegressor([n_epochs, batch_size, ...])	Multi Layer Perceptron Network (MLP), as described in [Rd2c369cc4f1f-1].
mlp.MLPRegressorTorch([hidden_dim, ...])	Multi Layer Perceptron Network (MLP), as described in [Ra6642a4e6bf6-1].
resnet.ResNetRegressor([n_epochs, ...])	Residual Neural Network Regressor adopted from [1].
rnn.SimpleRNNRegressor([n_epochs, ...])	Simple recurrent neural network.
rnn.SimpleRNNRegressorTorch([hidden_dim, ...])	Simple recurrent neural network in PyTorch for time series regression.
tapnet.TapNetRegressor([n_epochs, ...])	Time series attentional prototype network (TapNet), as described in [1].
tapnet.TapNetRegressorTorch([filter_sizes, ...])	TapNet regressor in PyTorch.

Distance-based

KNeighborsTimeSeriesRegressor([n_neighbors, ...])

K-nearest neighbours Time Series Regressor.

Dummy

DummyRegressor([strategy, constant, quantile])

DummyRegressor makes predictions that ignore the input features.

Interval-based

TimeSeriesForestRegressor([min_interval, ...])

Time series forest regressor.

Kernel-based

TimeSeriesSVRTslearn([C, kernel, degree, ...])	Time Series Suppoer Vector Regressor, from tslearn.
RocketRegressor([num_kernels, ...])	Regressor wrapped for the Rocket transformer using RidgeCV regressor.

Base

BaseRegressor()

Abstract base class for time series regressors.

BaseDeepRegressor()

Abstract base class for deep learning time series regression.