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| # artifact for log file | |
| LOG_ENTRY_DIR = "Log_entry" | |
| # artifact for connection | |
| BUNDLE_NAME = "secure-connect-oil.zip" | |
| ROOT_PATH = "D:/msn/pycharm_projects/Brentprice/secure-connect-oil.zip" | |
| # artifact for csv file:) | |
| CSV_FILE = "Brent_oil.csv" | |
| CSV_DIR = "Csv" | |
| # app file artifact | |
| PLOT_DIR = "static" | |
| COMBINE_PLOT = "combined_price_plot.png" | |
| # Trained model directory: | |
| MODEL_FILENAME = "SARIMAX_FORCAST_MODEL.joblib" | |
| MAIN_MODEL_DIR = "Saved_Model_dir" | |
| # SARIMAX Model initialization | |
| ORDER = (1, 1, 1) | |
| SEASONAL_ORDER = (1, 1, 1, 7) | |
| # support module artifact | |
| FORECAST_DAY = 7 # give 7 days prediction customize time frame | |
| """ | |
| Note: ORDER = (p, d, q) SEASONAL_ORDER = (P, D, Q, s) | |
| # P = 1 P: Autoregressive order at the seasonal frequency. | |
| # D = 1 D: Order of seasonal differencing. | |
| # Q = 1 Q: Moving average order at the seasonal frequency. | |
| # s = 7 s: Window size. (keep it small) | |
| # p = 1 p:(AutoRegressive order) if p=2, the model uses the two most recent observations to predict the current one. | |
| # d = 1 d:(Integrated order) | |
| # q = 1 q: the model includes the most recent forecast error in the prediction. | |
| """ | |