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jmaslek
@@ -10,7 +10,7 @@
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<meta name="description" content="To obtain charts, make sure to add chart=True as the last parameter
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Get underlying data forecast.expo(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, trend: str = ‘A’, seasonal: str = ‘A’, seasonal_periods: int = 7, dampen: str = ‘F’, n_predict: int = 30, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[list[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], Optional[float], Any] Performs Probabilistic Exponential Smoothing forecasting This is a wrapper around statsmodels Holt-Winters' Exponential Smoothing; we refer to this link for the original and more complete documentation of the parameters.">
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Get underlying data forecast.expo(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, trend: str = ‘A’, seasonal: str = ‘A’, seasonal_periods: int = 7, dampen: str = ‘F’, n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[list[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], Optional[float], Any] Performs Probabilistic Exponential Smoothing forecasting This is a wrapper around statsmodels Holt-Winters' Exponential Smoothing; we refer to this link for the original and more complete documentation of the parameters.">
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@@ -47408,9 +47408,9 @@ code, img {
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<h3 id="forecastexpodata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--30-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any">
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forecast.expo(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, trend: str = ‘A’, seasonal: str = ‘A’, seasonal_periods: int = 7, dampen: str = ‘F’, n_predict: int = 30, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[list[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], Optional[float], Any]
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<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/expo/#forecastexpodata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--30-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.expo(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, trend: str = ‘A’, seasonal: str = ‘A’, seasonal_periods: int = 7, dampen: str = ‘F’, n_predict: int = 30, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[list[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], Optional[float], Any]" href="#forecastexpodata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--30-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any">
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<h3 id="forecastexpodata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--5-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any">
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forecast.expo(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, trend: str = ‘A’, seasonal: str = ‘A’, seasonal_periods: int = 7, dampen: str = ‘F’, n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[list[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], Optional[float], Any]
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<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/expo/#forecastexpodata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--5-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.expo(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, trend: str = ‘A’, seasonal: str = ‘A’, seasonal_periods: int = 7, dampen: str = ‘F’, n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[list[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], Optional[float], Any]" href="#forecastexpodata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--5-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any">
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</a>
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<h3 id="forecastexpodata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--30-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
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forecast.expo(data: Union[pandas.core.frame.DataFrame, pandas.core.series.Series], target_column: str = ‘close’, dataset_name: str = ‘’, trend: str = ‘A’, seasonal: str = ‘A’, seasonal_periods: int = 7, dampen: str = ‘F’, n_predict: int = 30, start_window: float = 0.85, forecast_horizon: int = 5, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)
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<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/expo/#forecastexpodata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--30-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.expo(data: Union[pandas.core.frame.DataFrame, pandas.core.series.Series], target_column: str = ‘close’, dataset_name: str = ‘’, trend: str = ‘A’, seasonal: str = ‘A’, seasonal_periods: int = 7, dampen: str = ‘F’, n_predict: int = 30, start_window: float = 0.85, forecast_horizon: int = 5, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)" href="#forecastexpodata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--30-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
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<h3 id="forecastexpodata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--5-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
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forecast.expo(data: Union[pandas.core.frame.DataFrame, pandas.core.series.Series], target_column: str = ‘close’, dataset_name: str = ‘’, trend: str = ‘A’, seasonal: str = ‘A’, seasonal_periods: int = 7, dampen: str = ‘F’, n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)
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<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/expo/#forecastexpodata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--5-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.expo(data: Union[pandas.core.frame.DataFrame, pandas.core.series.Series], target_column: str = ‘close’, dataset_name: str = ‘’, trend: str = ‘A’, seasonal: str = ‘A’, seasonal_periods: int = 7, dampen: str = ‘F’, n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)" href="#forecastexpodata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---trend-str--a-seasonal-str--a-seasonal_periods-int--7-dampen-str--f-n_predict-int--5-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
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<svg class="icon gdoc_link"><use xlink:href="#gdoc_link"></use></svg>
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@@ -10,7 +10,7 @@
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<meta name="description" content="To obtain charts, make sure to add chart=True as the last parameter
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Get underlying data forecast.tft(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, n_predict: int = 30, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, input_chunk_length: int = 14, output_chunk_length: int = 5, hidden_size: int = 16, lstm_layers: int = 1, num_attention_heads: int = 4, full_attention: bool = False, dropout: float = 0.1, hidden_continuous_size: int = 8, n_epochs: int = 200, batch_size: int = 32, model_save_name: str = ‘tft_model’, force_reset: bool = True, save_checkpoints: bool = True) -> Tuple[List[darts.">
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Get underlying data forecast.tft(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, n_predict: int = 5, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, input_chunk_length: int = 14, output_chunk_length: int = 5, hidden_size: int = 16, lstm_layers: int = 1, num_attention_heads: int = 4, full_attention: bool = False, dropout: float = 0.1, hidden_continuous_size: int = 8, n_epochs: int = 200, batch_size: int = 32, model_save_name: str = ‘tft_model’, force_reset: bool = True, save_checkpoints: bool = True) -> Tuple[List[darts.">
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<h3 id="forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-n_predict-int--30-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any">
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forecast.tft(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, n_predict: int = 30, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, input_chunk_length: int = 14, output_chunk_length: int = 5, hidden_size: int = 16, lstm_layers: int = 1, num_attention_heads: int = 4, full_attention: bool = False, dropout: float = 0.1, hidden_continuous_size: int = 8, n_epochs: int = 200, batch_size: int = 32, model_save_name: str = ‘tft_model’, force_reset: bool = True, save_checkpoints: bool = True) -> Tuple[List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], Optional[float], Any]
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<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/tft/#forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-n_predict-int--30-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.tft(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, n_predict: int = 30, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, input_chunk_length: int = 14, output_chunk_length: int = 5, hidden_size: int = 16, lstm_layers: int = 1, num_attention_heads: int = 4, full_attention: bool = False, dropout: float = 0.1, hidden_continuous_size: int = 8, n_epochs: int = 200, batch_size: int = 32, model_save_name: str = ‘tft_model’, force_reset: bool = True, save_checkpoints: bool = True) -> Tuple[List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], Optional[float], Any]" href="#forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-n_predict-int--30-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any">
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<h3 id="forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-n_predict-int--5-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any">
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forecast.tft(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, n_predict: int = 5, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, input_chunk_length: int = 14, output_chunk_length: int = 5, hidden_size: int = 16, lstm_layers: int = 1, num_attention_heads: int = 4, full_attention: bool = False, dropout: float = 0.1, hidden_continuous_size: int = 8, n_epochs: int = 200, batch_size: int = 32, model_save_name: str = ‘tft_model’, force_reset: bool = True, save_checkpoints: bool = True) -> Tuple[List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], Optional[float], Any]
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<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/tft/#forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-n_predict-int--5-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.tft(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, n_predict: int = 5, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, input_chunk_length: int = 14, output_chunk_length: int = 5, hidden_size: int = 16, lstm_layers: int = 1, num_attention_heads: int = 4, full_attention: bool = False, dropout: float = 0.1, hidden_continuous_size: int = 8, n_epochs: int = 200, batch_size: int = 32, model_save_name: str = ‘tft_model’, force_reset: bool = True, save_checkpoints: bool = True) -> Tuple[List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], Optional[float], Any]" href="#forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-n_predict-int--5-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-optionalfloat-any">
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<h3 id="forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-dataset_name-str---n_predict-int--30-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
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forecast.tft(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, dataset_name: str = ‘’, n_predict: int = 30, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, input_chunk_length: int = 14, output_chunk_length: int = 5, hidden_size: int = 16, lstm_layers: int = 1, num_attention_heads: int = 4, full_attention: bool = False, dropout: float = 0.1, hidden_continuous_size: int = 8, n_epochs: int = 200, batch_size: int = 32, model_save_name: str = ‘tft_model’, force_reset: bool = True, save_checkpoints: bool = True, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)
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<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/tft/#forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-dataset_name-str---n_predict-int--30-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.tft(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, dataset_name: str = ‘’, n_predict: int = 30, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, input_chunk_length: int = 14, output_chunk_length: int = 5, hidden_size: int = 16, lstm_layers: int = 1, num_attention_heads: int = 4, full_attention: bool = False, dropout: float = 0.1, hidden_continuous_size: int = 8, n_epochs: int = 200, batch_size: int = 32, model_save_name: str = ‘tft_model’, force_reset: bool = True, save_checkpoints: bool = True, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)" href="#forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-dataset_name-str---n_predict-int--30-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
|
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<h3 id="forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-dataset_name-str---n_predict-int--5-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
|
||||
forecast.tft(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, dataset_name: str = ‘’, n_predict: int = 5, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, input_chunk_length: int = 14, output_chunk_length: int = 5, hidden_size: int = 16, lstm_layers: int = 1, num_attention_heads: int = 4, full_attention: bool = False, dropout: float = 0.1, hidden_continuous_size: int = 8, n_epochs: int = 200, batch_size: int = 32, model_save_name: str = ‘tft_model’, force_reset: bool = True, save_checkpoints: bool = True, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)
|
||||
<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/tft/#forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-dataset_name-str---n_predict-int--5-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.tft(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, dataset_name: str = ‘’, n_predict: int = 5, past_covariates: str = None, train_split: float = 0.85, forecast_horizon: int = 5, input_chunk_length: int = 14, output_chunk_length: int = 5, hidden_size: int = 16, lstm_layers: int = 1, num_attention_heads: int = 4, full_attention: bool = False, dropout: float = 0.1, hidden_continuous_size: int = 8, n_epochs: int = 200, batch_size: int = 32, model_save_name: str = ‘tft_model’, force_reset: bool = True, save_checkpoints: bool = True, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)" href="#forecasttftdata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-dataset_name-str---n_predict-int--5-past_covariates-str--none-train_split-float--085-forecast_horizon-int--5-input_chunk_length-int--14-output_chunk_length-int--5-hidden_size-int--16-lstm_layers-int--1-num_attention_heads-int--4-full_attention-bool--false-dropout-float--01-hidden_continuous_size-int--8-n_epochs-int--200-batch_size-int--32-model_save_name-str--tft_model-force_reset-bool--true-save_checkpoints-bool--true-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
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<svg class="icon gdoc_link"><use xlink:href="#gdoc_link"></use></svg>
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|
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@@ -10,7 +10,7 @@
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<meta name="description" content="To obtain charts, make sure to add chart=True as the last parameter
|
||||
Get underlying data forecast.theta(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, seasonal: str = ‘M’, seasonal_periods: int = 7, n_predict: int = 30, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], float, float, Any] Performs Theta forecasting An implementation of the 4Theta method with configurable theta parameter.
|
||||
Get underlying data forecast.theta(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, seasonal: str = ‘M’, seasonal_periods: int = 7, n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], float, float, Any] Performs Theta forecasting An implementation of the 4Theta method with configurable theta parameter.
|
||||
https://unit8co.github.io/darts/generated_api/darts.models.forecasting.theta.html Parameters ---------- data : Union[pd.">
|
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|
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@@ -47409,9 +47409,9 @@ code, img {
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</h2>
|
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|
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<h3 id="forecastthetadata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-seasonal-str--m-seasonal_periods-int--7-n_predict-int--30-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-float-float-any">
|
||||
forecast.theta(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, seasonal: str = ‘M’, seasonal_periods: int = 7, n_predict: int = 30, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], float, float, Any]
|
||||
<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/theta/#forecastthetadata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-seasonal-str--m-seasonal_periods-int--7-n_predict-int--30-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-float-float-any" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.theta(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, seasonal: str = ‘M’, seasonal_periods: int = 7, n_predict: int = 30, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], float, float, Any]" href="#forecastthetadata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-seasonal-str--m-seasonal_periods-int--7-n_predict-int--30-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-float-float-any">
|
||||
<h3 id="forecastthetadata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-seasonal-str--m-seasonal_periods-int--7-n_predict-int--5-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-float-float-any">
|
||||
forecast.theta(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, seasonal: str = ‘M’, seasonal_periods: int = 7, n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], float, float, Any]
|
||||
<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/theta/#forecastthetadata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-seasonal-str--m-seasonal_periods-int--7-n_predict-int--5-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-float-float-any" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.theta(data: Union[pandas.core.series.Series, pandas.core.frame.DataFrame], target_column: str = ‘close’, seasonal: str = ‘M’, seasonal_periods: int = 7, n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5) -> Tuple[List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], List[darts.timeseries.TimeSeries], float, float, Any]" href="#forecastthetadata-unionpandascoreseriesseries-pandascoreframedataframe-target_column-str--close-seasonal-str--m-seasonal_periods-int--7-n_predict-int--5-start_window-float--085-forecast_horizon-int--5---tuplelistdartstimeseriestimeseries-listdartstimeseriestimeseries-listdartstimeseriestimeseries-float-float-any">
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@@ -47461,9 +47461,9 @@ Any
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</h2>
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<h3 id="forecastthetadata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---seasonal-str--m-seasonal_periods-int--7-n_predict-int--30-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
|
||||
forecast.theta(data: Union[pandas.core.frame.DataFrame, pandas.core.series.Series], target_column: str = ‘close’, dataset_name: str = ‘’, seasonal: str = ‘M’, seasonal_periods: int = 7, n_predict: int = 30, start_window: float = 0.85, forecast_horizon: int = 5, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)
|
||||
<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/theta/#forecastthetadata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---seasonal-str--m-seasonal_periods-int--7-n_predict-int--30-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.theta(data: Union[pandas.core.frame.DataFrame, pandas.core.series.Series], target_column: str = ‘close’, dataset_name: str = ‘’, seasonal: str = ‘M’, seasonal_periods: int = 7, n_predict: int = 30, start_window: float = 0.85, forecast_horizon: int = 5, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)" href="#forecastthetadata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---seasonal-str--m-seasonal_periods-int--7-n_predict-int--30-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
|
||||
<h3 id="forecastthetadata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---seasonal-str--m-seasonal_periods-int--7-n_predict-int--5-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
|
||||
forecast.theta(data: Union[pandas.core.frame.DataFrame, pandas.core.series.Series], target_column: str = ‘close’, dataset_name: str = ‘’, seasonal: str = ‘M’, seasonal_periods: int = 7, n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)
|
||||
<a data-clipboard-text="https://openbb-finance.github.io/OpenBBTerminal/SDK/forecast/theta/#forecastthetadata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---seasonal-str--m-seasonal_periods-int--7-n_predict-int--5-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue" class="gdoc-page__anchor gdoc-page__anchor--right clip" aria-label="Anchor forecast.theta(data: Union[pandas.core.frame.DataFrame, pandas.core.series.Series], target_column: str = ‘close’, dataset_name: str = ‘’, seasonal: str = ‘M’, seasonal_periods: int = 7, n_predict: int = 5, start_window: float = 0.85, forecast_horizon: int = 5, export: str = ‘’, residuals: bool = False, forecast_only: bool = False, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None, naive: bool = False, export_pred_raw: bool = False, external_axes: Optional[List[axes]] = None, chart=True)" href="#forecastthetadata-unionpandascoreframedataframe-pandascoreseriesseries-target_column-str--close-dataset_name-str---seasonal-str--m-seasonal_periods-int--7-n_predict-int--5-start_window-float--085-forecast_horizon-int--5-export-str---residuals-bool--false-forecast_only-bool--false-start_date-optionaldatetimedatetime--none-end_date-optionaldatetimedatetime--none-naive-bool--false-export_pred_raw-bool--false-external_axes-optionallistaxes--none-charttrue">
|
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<svg class="icon gdoc_link"><use xlink:href="#gdoc_link"></use></svg>
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|
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