def main(crowdflower_output, num_judgments):
    """
    this script computes the agreement of judgments given in the crowdflower
    job using a metric called Fleiss kappa
    """
    cf_results = read_full_results(crowdflower_output)
    mat = compute_matrix(cf_results, num_judgments)
    print computeFleissKappa(mat)
예제 #2
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def main(crowdflower_output, num_judgments):
    """
    this script computes the agreement of judgments given in the crowdflower
    job using a metric called Fleiss kappa
    """
    cf_results = read_full_results(crowdflower_output)
    mat = compute_matrix(cf_results, num_judgments)
    print computeFleissKappa(mat)
def main(crowdflower_output, num_judgments):
    """
    this script computes the agreement of judgments given in the crowdflower
    job using a metric called Fleiss kappa
    :param file crowdflower_output: CSV file containing the results from crowdflower
    :param int num_judgments: Consider only this number of results, skip if not enough
    """
    cf_results = read_full_results(crowdflower_output)
    mat = compute_matrix(cf_results, num_judgments)
    print computeFleissKappa(mat)
def main(crowdflower_output, num_judgments):
    """
    this script computes the agreement of judgments given in the crowdflower
    job using a metric called Fleiss kappa
    :param file crowdflower_output: CSV file containing the results from crowdflower
    :param int num_judgments: Consider only this number of results, skip if not enough
    """
    cf_results = read_full_results(crowdflower_output)
    mat = compute_matrix(cf_results, num_judgments)
    print computeFleissKappa(mat)
def main(crowdflower_output, num_judgments):
    cf_results = read_full_results(crowdflower_output)
    mat = compute_matrix(cf_results, num_judgments)
    print computeFleissKappa(mat)