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)],
    }
def metta_config ( quarter , num_dimensions ) : 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 ) ] , }
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