Ctrl+K
Logo image Logo image

Site Navigation

  • Get Started
  • Documentation
  • Installation
  • API Reference
  • Get Involved
  • Development
  • About

Site Navigation

  • Get Started
  • Documentation
  • Installation
  • API Reference
  • Get Involved
  • Development
  • About
Ctrl+K

Section Navigation

  • Base
    • BaseObject
    • BaseEstimator
  • Forecasting
    • ForecastingHorizon
    • NaiveForecaster
    • NaiveVariance
    • TrendForecaster
    • PolynomialTrendForecaster
    • STLForecaster
    • ExponentialSmoothing
    • AutoETS
    • AutoARIMA
    • ARIMA
    • StatsForecastAutoARIMA
    • ThetaForecaster
    • BATS
    • TBATS
    • Croston
    • Prophet
    • UnobservedComponents
    • ColumnEnsembleForecaster
    • EnsembleForecaster
    • AutoEnsembleForecaster
    • StackingForecaster
    • TransformedTargetForecaster
    • ForecastingPipeline
    • DirectTabularRegressionForecaster
    • DirectTimeSeriesRegressionForecaster
    • MultioutputTabularRegressionForecaster
    • MultioutputTimeSeriesRegressionForecaster
    • RecursiveTabularRegressionForecaster
    • RecursiveTimeSeriesRegressionForecaster
    • DirRecTabularRegressionForecaster
    • DirRecTimeSeriesRegressionForecaster
    • MultiplexForecaster
    • make_reduction
    • OnlineEnsembleForecaster
    • NormalHedgeEnsemble
    • NNLSEnsemble
    • CutoffSplitter
    • SingleWindowSplitter
    • SlidingWindowSplitter
    • ExpandingWindowSplitter
    • ForecastingGridSearchCV
    • ForecastingRandomizedSearchCV
    • temporal_train_test_split
    • evaluate
    • VAR
    • SARIMAX
  • Time series annotation
    • PyODAnnotator
  • Time series classification
    • ColumnEnsembleClassifier
    • IndividualBOSS
    • BOSSEnsemble
    • ContractableBOSS
    • WEASEL
    • MUSE
    • IndividualTDE
    • TemporalDictionaryEnsemble
    • KNeighborsTimeSeriesClassifier
    • ElasticEnsemble
    • ProximityForest
    • ProximityTree
    • ProximityStump
    • HIVECOTEV1
    • HIVECOTEV2
    • TimeSeriesForestClassifier
    • SupervisedTimeSeriesForest
    • CanonicalIntervalForest
    • DrCIF
    • RandomIntervalSpectralEnsemble
    • ShapeletTransformClassifier
    • Arsenal
    • Catch22Classifier
    • MatrixProfileClassifier
    • TSFreshClassifier
    • SignatureClassifier
    • FreshPRINCE
    • SummaryClassifier
    • RandomIntervalClassifier
  • Time series regression
    • ComposableTimeSeriesForestRegressor
    • TimeSeriesForestRegressor
  • Time series clustering
    • BaseClusterer
    • TimeSeriesLloyds
    • TimeSeriesKMeans
    • TimeSeriesKMedoids
    • TimeSeriesKShapes
    • TimeSeriesKernelKMeans
  • Series-as-features tools
    • FeatureUnion
    • PresplitFilesCV
    • SingleSplit
  • Time series transformations
    • PAA
    • SFA
    • SAX
    • DerivativeSlopeTransformer
    • PlateauFinder
    • RandomIntervalFeatureExtractor
    • FittedParamExtractor
    • TSFreshRelevantFeatureExtractor
    • TSFreshFeatureExtractor
    • Catch22
    • ColumnTransformer
    • ColumnConcatenator
    • SeriesToSeriesRowTransformer
    • SeriesToPrimitivesRowTransformer
    • make_row_transformer
    • MatrixProfile
    • PCATransformer
    • Tabularizer
    • Rocket
    • MiniRocket
    • MiniRocketMultivariate
    • IntervalSegmenter
    • RandomIntervalSegmenter
    • SignatureTransformer
    • Detrender
    • Deseasonalizer
    • ConditionalDeseasonalizer
    • STLTransformer
    • TabularToSeriesAdaptor
    • BoxCoxTransformer
    • LogTransformer
    • ScaledLogitTransformer
    • ClaSPTransformer
    • Differencer
    • AutoCorrelationTransformer
    • PartialAutoCorrelationTransformer
    • CosineTransformer
    • ExponentTransformer
    • SqrtTransformer
    • MatrixProfileTransformer
    • Imputer
    • DateTimeFeatures
    • WindowSummarizer
    • HampelFilter
    • TransformerPipeline
    • FeatureUnion
    • FitInTransform
    • OptionalPassthrough
    • ColumnwiseTransformer
    • ThetaLinesTransformer
    • InvertAugmenter
    • RandomSamplesAugmenter
    • ReverseAugmenter
    • WhiteNoiseAugmenter
    • SummaryTransformer
    • FeatureSelection
    • STLBootstrapTransformer
    • MovingBlockBootstrapTransformer
  • Performance metrics
    • MeanAbsoluteScaledError
    • MedianAbsoluteScaledError
    • MeanSquaredScaledError
    • MedianSquaredScaledError
    • MeanAbsoluteError
    • MeanSquaredError
    • MedianAbsoluteError
    • MedianSquaredError
    • GeometricMeanAbsoluteError
    • GeometricMeanSquaredError
    • MeanAbsolutePercentageError
    • MedianAbsolutePercentageError
    • MeanSquaredPercentageError
    • MedianSquaredPercentageError
    • MeanRelativeAbsoluteError
    • MedianRelativeAbsoluteError
    • GeometricMeanRelativeAbsoluteError
    • GeometricMeanRelativeSquaredError
    • MeanAsymmetricError
    • MeanLinexError
    • RelativeLoss
    • make_forecasting_scorer
    • mean_absolute_scaled_error
    • median_absolute_scaled_error
    • mean_squared_scaled_error
    • median_squared_scaled_error
    • mean_absolute_error
    • mean_squared_error
    • median_absolute_error
    • median_squared_error
    • geometric_mean_absolute_error
    • geometric_mean_squared_error
    • mean_absolute_percentage_error
    • median_absolute_percentage_error
    • mean_squared_percentage_error
    • median_squared_percentage_error
    • mean_relative_absolute_error
    • median_relative_absolute_error
    • geometric_mean_relative_absolute_error
    • geometric_mean_relative_squared_error
    • mean_asymmetric_error
    • mean_linex_error
    • relative_loss
  • Datasets
    • load_airline
    • load_arrow_head
    • load_gunpoint
    • load_osuleaf
    • load_italy_power_demand
    • load_basic_motions
    • load_japanese_vowels
    • load_shampoo_sales
    • load_longley
    • load_lynx
    • load_acsf1
    • load_uschange
    • load_UCR_UEA_dataset
    • load_macroeconomic
  • Utility functions
    • plot_series
    • plot_lags
    • plot_correlations
    • are_columns_nested
    • from_nested_to_2d_array
    • from_2d_array_to_nested
    • from_3d_numpy_to_2d_array
    • from_3d_numpy_to_nested
    • from_nested_to_3d_numpy
    • from_multi_index_to_3d_numpy
    • from_3d_numpy_to_multi_index
    • from_multi_index_to_nested
    • from_nested_to_multi_index
    • from_nested_to_long
    • from_long_to_nested
  • Exceptions
    • NotEvaluatedError
    • NotFittedError
    • FitFailedWarning

Time series regression#

The sktime.regression module contains algorithms and composition tools for time series regression.

Implements sktime estimators for time series regression.

Composition#

ComposableTimeSeriesForestRegressor([…])

Time-Series Forest Regressor.

Interval-based#

TimeSeriesForestRegressor([min_interval, …])

Time series forest regressor.

On this page
  • Composition
  • Interval-based

© Copyright 2019 - 2021 (BSD-3-Clause License).

Created using Sphinx 4.1.1.