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Data Partitioning: Split the data into train and test. The training data should contain 8 0 % of the full data and the test data

Data Partitioning: Split the data into train and test. The training data should contain 80% of the full data and the test data should contain the most recent 20% of the full data. Same data partition as used in the last question.
Build a Simple Exponential Smoothing model [set the 'initialization_method' parameter value as 'estimated' and when using the '.fit' command, please do make sure that the parameter is optimized=True] and calculate the Root Mean Squared Error on the test data. For this particular model, take logarithm on both the training and test data.
Hint: Use the function np.log(), where numpy has been imported under the alias np.

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