API Reference

Complete API reference for all Yohou classes and functions. Use the search box to filter, or click any name to see full documentation.

Name	Type	Module	Description
AbsoluteGammaResidual	Class	yohou.metrics	Absolute gamma residual scorer using absolute relative errors.
AbsoluteQuantileResidual	Class	yohou.metrics	Absolute quantile residual scorer for interval forecasts.
AbsoluteResidual	Class	yohou.metrics	Absolute residual conformity scorer using unsigned prediction errors.
AbsoluteSeasonalReturn	Class	yohou.stationarity	Absolute seasonal return (difference) time series transformer.
Accuracy	Class	yohou.metrics	Categorical accuracy from class-probability forecasts.
add_interval	Function	yohou.utils	Add n intervals to a datetime (handles variable-length intervals).
all_displays	Function	yohou.utils	Get a list of all displays from `yohou`.
all_estimators	Function	yohou.utils	Get a list of all estimators from `yohou`.
all_functions	Function	yohou.utils	Get a list of all functions from `yohou`.
apply_default_layout	Function	yohou.plotting	Apply default layout configuration to a figure.
ASinhTransformer	Class	yohou.stationarity	Variance stabilization through arcsinh transform.
assert_request_equal	Function	yohou.testing	Assert metadata request matches expected dictionary.
assert_request_is_empty	Function	yohou.testing	Check if a metadata request dict is empty.
BaseClassProbaForecaster	Base Class	yohou.class_proba	Base class for class-probability forecasters.
BaseClassProbaScorer	Base Class	yohou.metrics	Base class for class-probability forecast metrics.
BaseConformityScorer	Base Class	yohou.metrics	Base class for conformal prediction conformity scorers.
BaseForecaster	Base Class	yohou.base	Base class for forecasters.
BaseHardLabelScorer	Base Class	yohou.metrics	Base class for confusion-matrix classification metrics.
BaseIntervalForecaster	Base Class	yohou.interval	Base class for interval forecasters.
BaseIntervalScorer	Base Class	yohou.metrics	Base class for interval forecast metrics.
BasePanelForecaster	Base Class	yohou.base	Mixin providing panel (dict of DataFrames) forecaster operations.
BasePointForecaster	Base Class	yohou.point	Base class for point forecasters.
BasePointScorer	Base Class	yohou.metrics	Base class for point forecast metrics.
BaseRankingScorer	Base Class	yohou.metrics	Base class for ranking classification metrics.
BaseReductionForecaster	Base Class	yohou.base	Base class for forecasters using reduction to supervised learning.
BaseScorer	Base Class	yohou.metrics	Base class for all forecasting metrics.
BaseSearchCV	Base Class	yohou.model_selection	Abstract base class for hyperparameter search with cross-validation.
BaseSimilarity	Base Class	yohou.interval	Base class for similarity measures used in interval forecasting.
BaseSplitter	Base Class	yohou.model_selection	Base class for yohou time series cross-validation splitters.
BaseStandardForecaster	Base Class	yohou.base	Mixin providing standard (single DataFrame) forecaster operations.
BaseTransformer	Base Class	yohou.base	Base class for time series transformers.
BoxCoxTransformer	Class	yohou.stationarity	Box-Cox power transformation time series transformer.
BrierScore	Class	yohou.metrics	Multi-class Brier score for class-probability forecasts.
build_category_map	Function	yohou.plotting	Build a sorted category-to-integer mapping from one or more series.
CalendarFeatureTransformer	Class	yohou.preprocessing	Extract calendar-based features from the time column.
CalibrationError	Class	yohou.metrics	Calibration Error for prediction intervals.
cast	Function	yohou.utils	Cast columns according to schema with integer rounding.
check_class_proba_classes_attribute	Function	yohou.testing	Check classes_ and n_classes_ attributes are populated correctly after fit.
check_class_proba_predict_returns_labels	Function	yohou.testing	Check predict() returns argmax class labels, not probabilities.
check_class_proba_prediction_bounds	Function	yohou.testing	Check all probability values are in [0, 1].
check_class_proba_prediction_structure	Function	yohou.testing	Check class-probability predictions have correct column structure.
check_class_proba_prediction_sums	Function	yohou.testing	Check probabilities sum to approximately 1.0 per row per target.
check_class_proba_prediction_types	Function	yohou.testing	Check class-proba forecaster has 'class_proba' in forecaster_type tag.
check_clone_preserves_forecaster_params	Function	yohou.testing	Check sklearn's clone() preserves init parameters.
check_continuity	Function	yohou.utils	Validate temporal continuity between consecutive DataFrames.
check_coverage_rates_parameter	Function	yohou.testing	Check coverage_rates is list of floats in [0, 1].
check_coverage_rates_validation	Function	yohou.testing	Check invalid coverage_rates raise ValueError during fit and predict.
check_cv	Function	yohou.model_selection	Input checker utility for building a cross-validator.
check_cv_alignment	Function	yohou.model_selection	Inspect how a CV splitter's test windows align with a forecasting horizon.
check_estimator_parameter	Function	yohou.testing	Check estimator parameter is sklearn BaseEstimator.
check_feature_names_out_match	Function	yohou.testing	Check get_feature_names_out() matches transform() output columns.
check_fit_idempotent	Function	yohou.testing	Check that fit(X).fit(X) equals fit(X).
check_fit_predict_with_X_forecast	Function	yohou.testing	Check fit + predict works with X_forecast provided.
check_fit_predict_with_X_future	Function	yohou.testing	Check fit + predict works with X_future provided.
check_fit_predict_without_exogenous	Function	yohou.testing	Check forecaster behavior when X_actual=None at fit time.
check_fit_sets_attributes	Function	yohou.testing	Check fit() sets required attributes.
check_fit_sets_forecaster_attributes	Function	yohou.testing	Check fit() sets required forecaster attributes.
check_fit_transform_equivalence	Function	yohou.testing	Check fit_transform(X) == fit(X).transform(X).
check_forecaster_methods_call_check_is_fitted	Function	yohou.testing	Check all forecaster methods (except fit) raise NotFittedError when unfitted.
check_forecaster_not_fitted_error	Function	yohou.testing	Check accessing fitted attributes before fit() raises NotFittedError.
check_forecaster_tags_accessible_before_fit	Function	yohou.testing	Check __sklearn_tags__() is accessible before fit().
check_forecaster_tags_match_capabilities	Function	yohou.testing	Check forecaster tags accurately reflect capabilities.
check_forecaster_tags_static_after_fit	Function	yohou.testing	Check forecaster tags remain static after fit().
check_forecasting_horizon_positive	Function	yohou.utils	Validate forecasting horizon is positive.
check_forecasting_horizon_validation	Function	yohou.testing	Check forecasting_horizon < 1 raises ValueError.
check_grid_search_exhaustive	Function	yohou.testing	Check GridSearchCV evaluates all parameter combinations.
check_grid_search_param_grid_validation	Function	yohou.testing	Check param_grid format is validated (dict or list of dicts).
check_groups	Function	yohou.utils	Validate and normalize panel group names for forecaster operations.
check_groups_exist	Function	yohou.utils	Validate all requested panel groups exist in fitted forecaster.
check_inputs	Function	yohou.utils	Validate that target and feature DataFrames have consistent time intervals.
check_insufficient_data_raises	Function	yohou.testing	Check behavior when data length < observation_horizon.
check_interval_bounds	Function	yohou.testing	Check upper >= lower for all coverage rates and time steps.
check_interval_consistency	Function	yohou.utils	Validate that a time series has uniform time spacing.
check_interval_prediction_columns	Function	yohou.testing	Check interval predictions have {col}_lower_{rate} and {col}_upper_{rate} format.
check_interval_prediction_types	Function	yohou.testing	Check interval forecaster has 'interval' in forecaster_type tag.
check_inverse_observe_transform_identity	Function	yohou.testing	Check inverse_transform(observe_transform(X)) ≈ X.
check_inverse_transform_identity	Function	yohou.testing	Check inverse_transform(transform(X)) ≈ X.
check_inverse_transform_round_trip	Function	yohou.testing	Check inverse_transform(transform(X)) ≈ X with shape validation.
check_memory_bounded	Function	yohou.testing	Check memory doesn't grow unbounded with sequential updates.
check_metadata_routing_default_request	Function	yohou.testing	Check that by default metadata routing request is empty.
check_metadata_routing_get_metadata_routing	Function	yohou.testing	Check that get_metadata_routing() is implemented correctly.
check_observation_horizon_after_fit	Function	yohou.testing	Check observation_horizon is valid after fit().
check_observation_horizon_not_fitted	Function	yohou.testing	Check observation_horizon behavior before fit().
check_observe_auto_rederives_step_columns	Function	yohou.testing	Check observe() re-derives step columns from stored raws.
check_observe_concatenates_memory	Function	yohou.testing	Check observe() appends new data and maintains horizon size.
check_observe_extends_observations	Function	yohou.testing	Check observe() extends observation buffers correctly.
check_observe_predict_interval_with_step_columns	Function	yohou.testing	Check observe_predict_interval works with step columns (lightweight).
check_observe_predict_with_step_columns	Function	yohou.testing	Check observe_predict works with step columns (lightweight).
check_observe_transform_equivalence	Function	yohou.testing	Check observe().transform() == fit().transform() for same final state.
check_observe_transform_sequential_consistency	Function	yohou.testing	Check observe_transform(A) then observe_transform(B) == observe_transform(A+B).
check_panel_data	Function	yohou.testing	Check cross-learning with panel data predicts all groups by default.
check_panel_data_support	Function	yohou.testing	Check transformer handles panel columns (panel data) correctly.
check_panel_group_preservation	Function	yohou.testing	Check that transformers preserve panel group names after transformation.
check_panel_groups_match	Function	yohou.utils	Validate that y and X_actual have compatible panel group structures.
check_panel_internal_consistency	Function	yohou.utils	Validate that all panel groups in a DataFrame have the same local column structure.
check_panel_invalid_group_raises	Function	yohou.testing	Check that invalid panel_group raises ValueError.
check_panel_single_group	Function	yohou.testing	Check cross-learning filters to specified panel group.
check_point_prediction_structure	Function	yohou.testing	Check point predictions have correct column structure.
check_point_prediction_types	Function	yohou.testing	Check point forecaster has 'point' in forecaster_type tag.
check_predict_time_columns	Function	yohou.testing	Check predictions have vintage_time and time columns.
check_predict_X_forecast_override	Function	yohou.testing	Check predict with X_forecast override produces different results.
check_prediction_types_property	Function	yohou.testing	Check forecaster_type tag is set correctly.
check_randomized_search_distributions	Function	yohou.testing	Check scipy.stats distributions work for parameter sampling.
check_randomized_search_n_iter	Function	yohou.testing	Check n_iter controls number of parameter combinations evaluated.
check_randomized_search_reproducibility	Function	yohou.testing	Check random_state produces same parameter samples.
check_recorded_metadata	Function	yohou.testing	Check whether the expected metadata is passed to the object's method.
check_reduction_strategy	Function	yohou.testing	Check reduction_strategy parameter is valid.
check_requires_exogenous_warns_on_X_future_X_forecast	Function	yohou.testing	Check that a forecaster with requires_exogenous=False warns when X_future/X_forecast provided.
check_rewind_propagates_to_transformers	Function	yohou.testing	Check rewind() propagates to transformers in forecaster.
check_rewind_replaces_observations	Function	yohou.testing	Check rewind() replaces observation buffers correctly.
check_rewind_transform_behavior	Function	yohou.testing	Check rewind_transform() behavior and contract.
check_rewind_updates_memory	Function	yohou.testing	Check rewind() updates _X_observed to last observation_horizon rows.
check_schema	Function	yohou.utils	Validate DataFrame schema and return with proper column ordering.
check_scorer_aggregation_methods	Function	yohou.testing	Check all aggregation_method combinations produce valid output.
check_scorer_column_selection	Function	yohou.utils	Subselect columns based on scorer configuration.
check_scorer_component_subselection	Function	yohou.testing	Check components filtering works correctly.
check_scorer_coverage_rate_subselection	Function	yohou.testing	Check coverage parameter filters interval predictions correctly.
check_scorer_lower_is_better	Function	yohou.testing	Check lower_is_better convention matches scoring direction.
check_scorer_methods_call_check_is_fitted	Function	yohou.testing	Check all scorer methods (except fit) raise NotFittedError when unfitted.
check_scorer_multi_vintage	Function	yohou.testing	Check that scorer produces a finite result on multi-vintage input.
check_scorer_panel_subselection	Function	yohou.testing	Check groups filtering works correctly.
check_scorer_parameter_validation	Function	yohou.testing	Check parameter validation raises ValueError for invalid inputs.
check_scorer_prediction_type_compatibility	Function	yohou.testing	Check scorer works with correct forecaster output type.
check_scorer_tags_accessible_before_fit	Function	yohou.testing	Check __sklearn_tags__() is callable on scorer instance.
check_scorer_tags_match_capabilities	Function	yohou.testing	Check tag values match actual scorer behavior.
check_scorer_tags_static_after_fit	Function	yohou.testing	Check tags remain unchanged after fit.
check_search_clone_preserves_params	Function	yohou.testing	Check sklearn clone() preserves search CV parameters.
check_search_cv_results_structure	Function	yohou.testing	Check cv_results_ has required structure.
check_search_error_score_handling	Function	yohou.testing	Check error_score parameter handles failing fits correctly.
check_search_fit_sets_attributes	Function	yohou.testing	Check fit() sets required search CV attributes.
check_search_interval_predict_delegates	Function	yohou.testing	Check predict_interval() works after interval search with refit.
check_search_method_availability	Function	yohou.testing	Check @available_if decorator logic with refit=True/False.
check_search_multimetric_scoring	Function	yohou.testing	Check multi-metric scoring with dict scorer works correctly.
check_search_not_fitted_error	Function	yohou.testing	Check accessing fitted attributes before fit() raises NotFittedError.
check_search_observe_delegates	Function	yohou.testing	Check observe() delegates to best_forecaster_.observe() correctly.
check_search_panel_data	Function	yohou.testing	Check groups parameter propagates correctly.
check_search_predict_delegates	Function	yohou.testing	Check predict() delegates to best_forecaster_.predict() correctly.
check_search_refit_false_no_forecaster	Function	yohou.testing	Check refit=False doesn't create best_forecaster_.
check_search_return_train_score	Function	yohou.testing	Check return_train_score=True adds train score keys to cv_results_.
check_search_rewind_delegates	Function	yohou.testing	Check rewind() delegates to best_forecaster_.rewind() correctly.
check_splitter_n_splits_consistency	Function	yohou.testing	Check get_n_splits() matches actual split count.
check_splitter_non_overlapping_tests	Function	yohou.testing	Check test sets don't overlap if produces_non_overlapping_tests=True.
check_splitter_panel_data_support	Function	yohou.testing	Check splitter handles panel data if supports_panel_data=True.
check_splitter_parameter_constraints	Function	yohou.testing	Check parameter constraints are enforced via sklearn validation.
check_splitter_produces_valid_indices	Function	yohou.testing	Check all train/test indices are valid row positions.
check_splitter_tags_accessible_before_fit	Function	yohou.testing	Check __sklearn_tags__() is callable on splitter instance.
check_splitter_tags_match_capabilities	Function	yohou.testing	Check tag values match actual splitter behavior.
check_splitter_tags_static_after_fit	Function	yohou.testing	Check tags remain unchanged after fit.
check_sufficient_rows	Function	yohou.utils	Validate DataFrame has sufficient rows for operation.
check_tags_accessible_before_fit	Function	yohou.testing	Check __sklearn_tags__() is accessible before fit().
check_tags_match_capabilities	Function	yohou.testing	Check tags accurately reflect transformer capabilities.
check_tags_static_after_fit	Function	yohou.testing	Check tags remain static (don't change) after fit().
check_time_column	Function	yohou.utils	Validate that time column exists, has proper dtype, no nulls, and is sorted.
check_transform_drops_warmup_rows	Function	yohou.testing	Check stateful transformers drop exactly observation_horizon rows.
check_transform_output_structure	Function	yohou.testing	Check transform() output has "time" column and valid structure.
check_transformer_methods_call_check_is_fitted	Function	yohou.testing	Check all transformer methods (except fit) raise NotFittedError when unfitted.
check_transformer_preserve_dtypes	Function	yohou.testing	Check transformer preserves input dtypes.
check_transformers_unfitted_stateless	Function	yohou.testing	Check stateless transformers work without fitting.
check_X_actual_required	Function	yohou.utils	Validate X_actual is provided when required for recursive prediction.
ClassProbaReductionForecaster	Class	yohou.class_proba	Class-probability forecaster using sklearn classifiers on tabularized time series.
clear_data_home	Function	yohou.datasets	Delete all the content of the data home cache.
ColumnForecaster	Class	yohou.compose	Applies different forecasters to different column subsets.
ColumnTransformer	Class	yohou.compose	Applies transformers to columns of a polars DataFrame.
combine_weight_vectors	Function	yohou.utils	Combine weight vectors multiplicatively and normalize.
compose_weights	Function	yohou.utils	Compose multiple weight functions by multiplication.
CompositeSimilarity	Class	yohou.interval	Combine multiple similarity measures into a single weight vector.
config_context	Function	yohou.plotting	Context manager to temporarily override plotting configuration.
ContinuousRankedProbabilityScore	Class	yohou.metrics	Continuous Ranked Probability Score (CRPS) for prediction intervals.
cross_val_predict	Function	yohou.model_selection	Generate cross-validated predictions for each fold.
cross_val_score	Function	yohou.model_selection	Evaluate a forecaster by cross-validation and return test scores.
cross_validate	Function	yohou.model_selection	Evaluate a forecaster by cross-validation and return test scores and timings.
DecompositionPipeline	Class	yohou.compose	Meta-forecaster that decomposes time series into sequential components.
dict_to_panel	Function	yohou.utils	Convert a dict of group DataFrames to a single DataFrame with prefixed columns.
DistanceSimilarity	Class	yohou.interval	Distance-based similarity using scipy metrics for weighting observations.
Downsampler	Class	yohou.preprocessing	Downsample time series to a lower frequency using aggregation.
EmpiricalCoverage	Class	yohou.metrics	Empirical coverage rate for prediction intervals.
ExpandingWindowSplitter	Class	yohou.model_selection	Expanding window time series cross-validation splitter.
exponential_decay_weight	Function	yohou.utils	Generate exponential decay weights giving more weight to recent times.
ExponentialMovingAverage	Class	yohou.preprocessing	Exponentially Weighted Moving Average (EWMA) transformer.
facet_figure	Function	yohou.plotting	Create a faceted subplot figure for panel or column data.
FBetaScore	Class	yohou.metrics	F-beta score from class-probability forecasts.
FeaturePipeline	Class	yohou.compose	A sequence of time series transformers.
FeatureUnion	Class	yohou.compose	Concatenates results of multiple transformer objects.
fetch_air_quality_classification	Function	yohou.datasets	Fetch a categorical air quality dataset derived from KDD Cup 2018.
fetch_demand_classification	Function	yohou.datasets	Fetch a categorical electricity demand dataset from Monash/Zenodo.
fetch_dominick	Function	yohou.datasets	Fetch the Dominick dataset from Monash/Zenodo.
fetch_electricity_demand	Function	yohou.datasets	Fetch the Australian Electricity Demand dataset from Monash/Zenodo.
fetch_hospital	Function	yohou.datasets	Fetch the Hospital dataset from Monash/Zenodo.
fetch_kdd_cup	Function	yohou.datasets	Fetch the KDD Cup 2018 air quality dataset from Monash/Zenodo.
fetch_pedestrian_counts	Function	yohou.datasets	Fetch the Melbourne Pedestrian Counts dataset from Monash/Zenodo.
fetch_sunspot	Function	yohou.datasets	Fetch the Sunspot dataset (without missing values) from Monash/Zenodo.
fetch_tourism_monthly	Function	yohou.datasets	Fetch the Tourism Monthly dataset from Monash/Zenodo.
fetch_tourism_quarterly	Function	yohou.datasets	Fetch the Tourism Quarterly dataset from Monash/Zenodo.
ForecastedFeatureForecaster	Class	yohou.compose	Meta-forecaster that chains feature forecasting into target forecasting.
FourierFeatureTransformer	Class	yohou.preprocessing	Generate Fourier harmonic features from the time column.
FourierSeasonalityForecaster	Class	yohou.stationarity	Forecast using Fourier series representation of seasonality.
FunctionTransformer	Class	yohou.preprocessing	Constructs a transformer from an arbitrary callable.
GammaResidual	Class	yohou.metrics	Gamma residual scorer using relative prediction errors.
get_categorical_columns	Function	yohou.utils	Get list of categorical column names from a DataFrame.
get_color_sequence	Function	yohou.plotting	Get color sequence for plotting multiple series.
get_config	Function	yohou.plotting	Return a copy of the current global plotting configuration.
get_data_home	Function	yohou.datasets	Return the path of the yohou data directory.
get_group_df	Function	yohou.utils	Extract and rename columns for a specific panel group.
get_numeric_columns	Function	yohou.utils	Get list of numeric column names from a DataFrame.
get_scorer	Function	yohou.metrics	Get a scorer instance by name.
GridSearchCV	Class	yohou.model_selection	Exhaustive search over specified parameter values for a forecaster.
grouped_legend_kwargs	Function	yohou.plotting	Build kwargs for a trace that belongs to a titled legend group.
HolidayFeatureTransformer	Class	yohou.preprocessing	Extract holiday indicator features from a user-provided holiday calendar.
inspect_panel	Function	yohou.utils	Inspect DataFrame columns to distinguish global and local (panel) data.
interval_to_timedelta	Function	yohou.utils	Convert fixed interval to timedelta, or None for variable intervals.
IntervalReductionForecaster	Class	yohou.interval	Interval forecaster using sklearn estimators on tabularized time series.
IntervalScore	Class	yohou.metrics	Interval Score (Winkler Score) for prediction intervals.
is_categorical_dtype	Function	yohou.utils	Check whether a polars dtype represents categorical data.
LagTransformer	Class	yohou.preprocessing	Create lagged features from time series data.
linear_decay_weight	Function	yohou.utils	Generate linear decay weights giving more weight to recent times.
linked_legendgroup_kwargs	Function	yohou.plotting	Build ``legendgroup`` / ``showlegend`` kwargs for linked traces.
LocalPanelForecaster	Class	yohou.compose	Fits independent forecaster clones per panel group.
LogLoss	Class	yohou.metrics	Logarithmic loss (cross-entropy) for class-probability forecasts.
LogTransformer	Class	yohou.stationarity	Logarithmic time series transformer.
make_exogenous_classification	Function	yohou.datasets	Generate a synthetic classification dataset with exogenous features.
make_exogenous_regression	Function	yohou.datasets	Generate a synthetic regression dataset with exogenous features.
make_scorer	Function	yohou.metrics	Create a scorer instance with custom parameters.
MaxAbsoluteError	Class	yohou.metrics	Maximum Absolute Error metric for point forecasts.
MaxAbsScaler	Class	yohou.preprocessing	Scale each feature by its maximum absolute value.
MeanAbsoluteError	Class	yohou.metrics	Mean Absolute Error metric for point forecasts.
MeanAbsolutePercentageError	Class	yohou.metrics	Mean Absolute Percentage Error metric for point forecasts.
MeanAbsoluteScaledError	Class	yohou.metrics	Mean Absolute Scaled Error metric for point forecasts.
MeanDirectionalAccuracy	Class	yohou.metrics	Mean Directional Accuracy metric for point forecasts.
MeanIntervalWidth	Class	yohou.metrics	Mean width of prediction intervals.
MeanLagTransformer	Class	yohou.preprocessing	Create mean-lagged features by averaging across lag multiples.
MeanSeasonalNaive	Class	yohou.point	Seasonal naive forecaster that averages values across past seasons.
MeanSquaredError	Class	yohou.metrics	Mean Squared Error metric for point forecasts.
MedianAbsoluteError	Class	yohou.metrics	Median Absolute Error metric for point forecasts.
MinMaxScaler	Class	yohou.preprocessing	Transform features by scaling each feature to a given range.
normalize_weights	Function	yohou.utils	Normalize weights so they sum to the number of elements.
Normalizer	Class	yohou.preprocessing	Normalize samples individually to unit norm.
NumericalDifferentiator	Class	yohou.preprocessing	Numerical differentiation transformer for time series signals.
NumericalFilter	Class	yohou.preprocessing	Apply digital IIR or FIR filters to time series data.
NumericalIntegrator	Class	yohou.preprocessing	Numerical integration transformer for time series signals.
OutlierPercentileHandler	Class	yohou.preprocessing	Handle outliers based on percentile thresholds.
OutlierThresholdHandler	Class	yohou.preprocessing	Handle outliers based on fixed threshold values.
palette_yohou	Function	yohou.plotting	Return the yohou color palette.
panel_aware_prefix	Function	yohou.utils	Add a prefix to a column name while preserving the panel group prefix.
panel_aware_rename	Function	yohou.utils	Apply a rename function to a column name while preserving the panel group prefix.
panel_aware_suffix	Function	yohou.utils	Add a suffix to a column name while preserving the panel group prefix.
parse_interval	Function	yohou.utils	Parse interval string into (multiplier, unit).
parse_tsf	Function	yohou.datasets	Parse a Monash ``.tsf`` file into a wide polars DataFrame.
PatternSeasonalityForecaster	Class	yohou.stationarity	Forecast using seasonal pattern extraction and repetition.
PinballLoss	Class	yohou.metrics	Pinball Loss (Quantile Score) for prediction intervals.
plot_autocorrelation	Function	yohou.plotting	Plot autocorrelation function (ACF) for time series.
plot_boxplot	Function	yohou.plotting	Plot boxplots grouped by time periods.
plot_calibration	Function	yohou.plotting	Plot calibration for interval or class-probability forecasts.
plot_correlation_heatmap	Function	yohou.plotting	Plot correlation matrix heatmap for multiple time series.
plot_cross_correlation	Function	yohou.plotting	Plot cross-correlation function (CCF) between time series pairs.
plot_cv_results_scatter	Function	yohou.plotting	Plot hyperparameter search results as a scatter plot.
plot_decomposition	Function	yohou.plotting	Plot time series decomposition as vertically stacked subplots.
plot_distribution	Function	yohou.plotting	Plot histogram with optional KDE overlay for one or more columns.
plot_forecast	Function	yohou.plotting	Plot forecasts with historical data and optional prediction intervals.
plot_group_scores	Function	yohou.plotting	Plot scores broken down by panel group.
plot_lag_scatter	Function	yohou.plotting	Plot scatter plots of y(t) vs y(t-lag) for analysing temporal dependencies.
plot_missing_data	Function	yohou.plotting	Visualize missing data patterns over time.
plot_outliers	Function	yohou.plotting	Plot time series with outlier points highlighted.
plot_partial_autocorrelation	Function	yohou.plotting	Plot partial autocorrelation function (PACF) for time series.
plot_phase	Function	yohou.plotting	Plot the phase of a time series.
plot_resampling_comparison	Function	yohou.plotting	Plot original vs resampled time series for comparison.
plot_residuals	Function	yohou.plotting	Plot diagnostic plots for model residuals.
plot_rolling_statistics	Function	yohou.plotting	Plot rolling window statistics (mean, std, min, max, median, quantiles).
plot_scatter_matrix	Function	yohou.plotting	Plot an N×N scatter-plot matrix.
plot_score_distribution	Function	yohou.plotting	Plot the distribution of per-timestep scorer values.
plot_score_heatmap	Function	yohou.plotting	Plot a 2D heatmap of scores across two forecast dimensions.
plot_score_per_step	Function	yohou.plotting	Plot scorer value by forecast horizon step.
plot_score_per_vintage	Function	yohou.plotting	Plot scorer value by forecast vintage (observed time).
plot_score_summary	Function	yohou.plotting	Plot a grouped bar chart comparing aggregate scores across models and scorers.
plot_score_time_series	Function	yohou.plotting	Plot scorer values over time for one or more forecasts.
plot_seasonal_heatmap	Function	yohou.plotting	Plot a 2-D heatmap of aggregated values across two time dimensions.
plot_seasonality	Function	yohou.plotting	Plot seasonal overlay.
plot_spectrum	Function	yohou.plotting	Plot periodogram (power spectral density) for frequency domain analysis.
plot_splits	Function	yohou.plotting	Plot cross-validation splits as a timeline visualization.
plot_subseasonality	Function	yohou.plotting	Plot seasonal subseries.
plot_time_series	Function	yohou.plotting	Plot basic line plots for one or more time series.
plot_time_weight	Function	yohou.plotting	Plot time-based weights as a time series visualization.
PointReductionForecaster	Class	yohou.point	Point forecaster using sklearn estimators on tabularized time series.
PolynomialFeatures	Class	yohou.preprocessing	Generate polynomial and interaction features.
PolynomialTrendForecaster	Class	yohou.stationarity	Forecast using polynomial trend extrapolation with ElasticNet regularization.
PowerTransformer	Class	yohou.preprocessing	Apply a power transform featurewise to make data more Gaussian-like.
PRAuC	Class	yohou.metrics	Precision-Recall AUC from class-probability forecasts.
Precision	Class	yohou.metrics	Precision from class-probability forecasts.
QuantileResidual	Class	yohou.metrics	Quantile residual scorer for interval forecasts.
QuantileTransformer	Class	yohou.preprocessing	Transform features using quantiles information.
R2Score	Class	yohou.metrics	R-squared (Coefficient of Determination) metric for point forecasts.
RandomizedSearchCV	Class	yohou.model_selection	Randomized search on hyperparameters.
RankedProbabilityScore	Class	yohou.metrics	Ranked Probability Score for class-probability forecasts.
Recall	Class	yohou.metrics	Recall (sensitivity) from class-probability forecasts.
record_metadata	Function	yohou.testing	Store passed metadata to a method of obj.
Residual	Class	yohou.metrics	Residual-based conformity scorer using signed prediction errors.
resolve_color_palette	Function	yohou.plotting	Resolve a user-provided color palette or fall back to the default.
resolve_dict_weights	Function	yohou.utils	Map a ``{key: weight}`` dict to an aligned numpy array.
resolve_panel_columns	Function	yohou.plotting	Resolve which panel columns to plot.
resolve_weight_to_array	Function	yohou.utils	Resolve a weight specification to a raw numpy array.
RobustScaler	Class	yohou.preprocessing	Scale features using statistics that are robust to outliers.
ROCAuC	Class	yohou.metrics	ROC AUC from class-probability forecasts.
RollingStatisticsTransformer	Class	yohou.preprocessing	Compute rolling window statistics for time series.
RootMeanSquaredError	Class	yohou.metrics	Root Mean Squared Error metric for point forecasts.
RootMeanSquaredScaledError	Class	yohou.metrics	Root Mean Squared Scaled Error metric for point forecasts.
seasonal_emphasis_weight	Function	yohou.utils	Generate weights emphasizing specific seasonal positions.
SeasonalDifferencing	Class	yohou.stationarity	Seasonal differencing time series transformer.
SeasonalImputer	Class	yohou.preprocessing	Seasonal decomposition-based imputation for missing values.
SeasonalLogDifferencing	Class	yohou.stationarity	Seasonal log differencing time series transformer.
SeasonalNaive	Class	yohou.point	Seasonal naive forecaster that repeats values from previous season.
SeasonalReturn	Class	yohou.stationarity	Seasonal percentage return time series transformer.
select_panel_columns	Function	yohou.utils	Select panel group columns and optionally global columns of a DataFrame.
set_config	Function	yohou.plotting	Set global plotting configuration.
SimpleImputer	Class	yohou.preprocessing	Simple imputation using sklearn's SimpleImputer.
SimpleTimeImputer	Class	yohou.preprocessing	Time series imputation using interpolation or filling methods.
SklearnScaler	Class	yohou.preprocessing	Wrapper to integrate sklearn scalers into the Yohou pipeline.
SklearnTransformer	Class	yohou.preprocessing	Wrapper to integrate sklearn transformers into the Yohou pipeline.
SlidingWindowFunctionTransformer	Class	yohou.preprocessing	Transform time series by applying a function over sliding windows.
SlidingWindowSplitter	Class	yohou.model_selection	Sliding window time series cross-validation splitter.
SplineTransformer	Class	yohou.preprocessing	Generate univariate B-spline bases for features.
SplitConformalForecaster	Class	yohou.interval	Split conformal forecaster implementation.
StandardScaler	Class	yohou.preprocessing	Standardize features by removing the mean and scaling to unit variance.
SymmetricMeanAbsolutePercentageError	Class	yohou.metrics	Symmetric Mean Absolute Percentage Error metric for point forecasts.
tabularize	Function	yohou.utils	Convert time series to tabular format using lags.
TemporalSimilarity	Class	yohou.interval	Temporal similarity using Fourier features for weighting observations.
TimeIndexTransformer	Class	yohou.preprocessing	Convert the time column to a numeric index with optional polynomial terms.
train_test_split	Function	yohou.model_selection	Split time series data into temporal train and test sets.
TransformedSpaceKNNImputer	Class	yohou.preprocessing	K-nearest neighbors imputation in a transformed feature space.
Upsampler	Class	yohou.preprocessing	Upsample time series to a higher frequency using interpolation.
validate_callable_signature	Function	yohou.utils	Validate that callable has valid signature for time weighting.
validate_column_names	Function	yohou.utils	Validate that __ separator is used only for panel data group names.
validate_forecaster_data	Function	yohou.utils	Validate and prepare input data for forecasters.
validate_plotting_data	Function	yohou.utils	Validate a DataFrame for plotting and resolve columns.
validate_plotting_params	Function	yohou.utils	Validate common plotting function parameters.
validate_scorer_data	Function	yohou.utils	Validate and prepare scorer input data.
validate_search_data	Function	yohou.utils	Validate input data for hyperparameter search (GridSearchCV, RandomizedSearchCV).
validate_splitter_data	Function	yohou.utils	Validate and prepare input data for time series splitters.
validate_time_weight	Function	yohou.utils	Validate time_weight parameter for forecasters and scorers.
validate_transformer_data	Function	yohou.utils	Validate data for transformers.
validate_weight_array	Function	yohou.utils	Validate a resolved weight array for NaN, negatives, infinities, and all-zero.
VotingClassProbaForecaster	Class	yohou.ensemble	Combines class-probability forecasters via voting.
VotingIntervalForecaster	Class	yohou.ensemble	Combines interval predictions from multiple forecasters.
VotingPointForecaster	Class	yohou.ensemble	Combines point predictions from multiple forecasters via averaging.
weighted_quantile	Function	yohou.interval	Compute weighted quantile using cumulative sum approach.
window_forecasts	Function	yohou.utils	Window forecast data into step-indexed columns using as-of vintage selection.
window_futures	Function	yohou.utils	Window known-future features into step-indexed columns.