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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def metta_config(quarter, num_dimensions):
 """Returns metta metadata for a quarter's SOC code classifier matrix Args: quarter (str) quarter, in format '2015Q1' num_dimensions (int) Number of features in matrix Returns: (dict) metadata suitable for metta.archive_train_test """

    first_day, last_day = quarter_boundaries(quarter)
    return {
        'start_time': first_day,
        'end_time': last_day,
        'prediction_window': 3, # ???
        'label_name': 'onet_soc_code',
        'label_type': 'categorical',
        'matrix_id': 'job_postings_{}'.format(quarter),
        'feature_names': ['doc2vec_{}'.format(i) for i in range(num_dimensions)],
    }