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91 lines
4.2 KiB
Markdown
Vendored
91 lines
4.2 KiB
Markdown
Vendored
---
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title: expo
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description: This page provides a comprehensive guide to the expo usage for executing
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a Probabilistic Exponential Smoothing forecast. Parameters and their usage are laid
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out, along with examples for reference.
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keywords:
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- Probabilistic Exponential Smoothing
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- forecast
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- expo
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- trend
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- dampen
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- naive
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- target_column
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- n_days
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- seasonal_periods
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- start_window
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- s_end_date
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- s_start_date
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- residuals
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- forecast_only
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- export_pred_raw
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- parameters
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- usage examples
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---
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import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
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<HeadTitle title="forecast /expo - Reference | OpenBB Terminal Docs" />
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Perform Probabilistic Exponential Smoothing forecast: https://unit8co.github.io/darts/generated_api/darts.models.forecasting.exponential_smoothing.html
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### Usage
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```python
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expo [--trend {N,A,M}] [--dampen DAMPEN] [--naive] [-d {}] [-c TARGET_COLUMN] [-n N_DAYS] [-s {N,A,M}] [-p SEASONAL_PERIODS] [-w START_WINDOW] [--end S_END_DATE] [--start S_START_DATE] [--residuals] [--forecast-only] [--export-pred-raw]
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```
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---
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## Parameters
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| Name | Description | Default | Optional | Choices |
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| ---- | ----------- | ------- | -------- | ------- |
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| trend | Trend: N: None, A: Additive, M: Multiplicative. | A | True | N, A, M |
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| dampen | Dampening | F | True | None |
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| naive | Show the naive baseline for a model. | False | True | None |
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| target_dataset | The name of the dataset you want to select | None | True | None |
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| target_column | The name of the specific column you want to use | close | True | None |
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| n_days | prediction days. | 5 | True | None |
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| seasonal | Seasonality: N: None, A: Additive, M: Multiplicative. | A | True | N, A, M |
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| seasonal_periods | Seasonal periods: 4: Quarterly, 7: Daily | 7 | True | None |
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| start_window | Start point for rolling training and forecast window. 0.0-1.0 | 0.85 | True | None |
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| s_end_date | The end date (format YYYY-MM-DD) to select for testing | None | True | None |
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| s_start_date | The start date (format YYYY-MM-DD) to select for testing | None | True | None |
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| residuals | Show the residuals for the model. | False | True | None |
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| forecast_only | Do not plot the historical data without forecasts. | False | True | None |
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| export_pred_raw | Export predictions to a csv file. | False | True | None |
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---
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## Examples
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```python
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2022 Jul 23, 10:36 (🦋) /forecast/ $ load GME_20220719_123734.csv -a GME
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2022 Jul 23, 10:52 (🦋) /forecast/ $ expo GME
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100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 115/115 [00:1600:00, 6.80it/s]
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Exponential smoothing obtains MAPE: 12.88%
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Actual price: $ 146.64
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┏━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
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┃ Datetime ┃ Prediction ┃
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┡━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
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│ 2022-07-19 00:00:00 │ $ 146.35 │
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├─────────────────────┼────────────┤
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│ 2022-07-20 00:00:00 │ $ 148.63 │
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├─────────────────────┼────────────┤
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│ 2022-07-21 00:00:00 │ $ 148.86 │
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├─────────────────────┼────────────┤
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│ 2022-07-22 00:00:00 │ $ 151.76 │
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├─────────────────────┼────────────┤
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│ 2022-07-25 00:00:00 │ $ 149.74 │
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└─────────────────────┴────────────┘
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```
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---
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