SeasonalNaiveHyperparams

seasonal_naive_model.SeasonalNaiveHyperparams · inherits PydanticBaseModel

(No class summary provided)

Attributes

Attribute	Type	Default	Description
sp	int	-	Seasonal period

SeasonalNaiveModel

seasonal_naive_model.SeasonalNaiveModel · inherits BaseModel

Seasonal Naive model implementation.

__init__(self, params: Dict[str, Any], settings: Dict[str, Any])

Initialize Seasonal Naive model with model-specific parameters.

Parameter	Type	Default	Description
params	Dict[str, Any]	-	(undocumented)
settings	Dict[str, Any]	-	(undocumented)

train(self, y_context: np.ndarray, y_target: np.ndarray, timestamps_context: np.ndarray, timestamps_target: np.ndarray, x_context: Optional[np.ndarray] = None, x_target: Optional[np.ndarray] = None, **kwargs: dict) -> "SeasonalNaiveModel"

Train the Seasonal Naive model on given data. For this model, "training" simply means storing the historical data for future lookups.

Parameters:

Parameter	Type	Default	Description
y_context	np.ndarray	-	Past target values (pd.Series or np.ndarray).
y_target	np.ndarray	-	Future target values (not used by this model, but included for compatibility).
timestamps_context	np.ndarray	-	Timestamps for y_context (not used).
timestamps_target	np.ndarray	-	Timestamps for y_target (not used).
x_context	Optional[np.ndarray]	None	(undocumented)
x_target	Optional[np.ndarray]	None	(undocumented)
**kwargs	dict	-	Additional keyword arguments.

Returns: Self (The fitted model instance.)

predict(self, y_context: np.ndarray, timestamps_context: np.ndarray, timestamps_target: np.ndarray, x_context: Optional[np.ndarray] = None, x_target: Optional[np.ndarray] = None, **kwargs: dict)

Make predictions using the trained Seasonal Naive model.

Parameters:

Parameter	Type	Default	Description
y_context	np.ndarray	-	Context time series values (pd.Series or np.ndarray).
timestamps_context	np.ndarray	-	Timestamps for context data.
timestamps_target	np.ndarray	-	Timestamps for target data.
x_context	Optional[np.ndarray]	None	(undocumented)
x_target	Optional[np.ndarray]	None	(undocumented)
**kwargs	dict	-	Additional keyword arguments.

Returns: np.ndarray (Model predictions with shape (num_series, forecast_horizon).)