.. _sphx_glr_auto_examples_arima_example_persisting_a_model.py: ========================= Persisting an ARIMA model ========================= This example demonstrates how we can persist an ARIMA model to disk after fitting it. It can then be loaded back up and used to generate forecasts. .. raw:: html
.. rst-class:: sphx-glr-script-out Out:: Predictions: array([21966.69715352, 25983.70920565, 30225.30978848, 35417.12496267, 13011.3618805 , 19639.41027742, 21506.58176159, 23674.33998321, 21685.76394174, 23669.77818948, 26955.35255979, 22755.2506162 , 19808.16131764, 23578.7818493 , 27845.86719673, 32923.89426476, 10475.6877784 , 17024.74533391, 18831.64797186, 20929.546713 , 18876.02414315, 20792.57512611, 24011.97546913, 19745.03906623, 16731.45362497, 20435.40470597, 24635.90938245, 29647.31030073, 7132.50096185, 13614.94373048, 15355.2376951 , 17386.52463115, 15266.3918605 , 17116.33182084, 20269.12156224, 15935.57434204, 12855.37819397, 16492.71851157, 20626.61245363, 25571.40262264, 2989.9825421 , 9405.81456517, 11079.49778624, 13044.1739777 , 10857.430463 , 12640.75967901, 15726.93867622, 11326.78071176, 8179.97381947, 11750.70339282, 15817.98659065]) | .. code-block:: python print(__doc__) # Author: Taylor Smith import pmdarima as pm from sklearn.externals import joblib # for persistence import os # ############################################################################# # Load the data and split it into separate pieces y = pm.datasets.load_wineind() train, test = y[:125], y[125:] # Fit an ARIMA arima = pm.ARIMA(order=(1, 1, 2), seasonal_order=(0, 1, 1, 12)) arima.fit(y) # ############################################################################# # Persist a model and create predictions after re-loading it pickle_tgt = "arima.pkl" try: # Pickle it joblib.dump(arima, pickle_tgt, compress=3) # Load the model up, create predictions arima_loaded = joblib.load(pickle_tgt) preds = arima_loaded.predict(n_periods=test.shape[0]) print("Predictions: %r" % preds) finally: # Remove the pickle file at the end of this example try: os.unlink(pickle_tgt) except OSError: pass **Total running time of the script:** ( 0 minutes 5.362 seconds) .. only :: html .. container:: sphx-glr-footer .. container:: sphx-glr-download :download:`Download Python source code: example_persisting_a_model.py ` .. container:: sphx-glr-download :download:`Download Jupyter notebook: example_persisting_a_model.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_