DFS（枝刈り込み）による統計的識別手法の最良組み合わせ抽出

statistical_identify_dfs.ipynb

To reduce total processing time by using multiprocessing

import multiprocessing as mp

def roc(v):
    """ calculate one pair, return (index, auc) """
    i, true, pred = v
    fpr, tpr, thresholds = metrics.roc_curve(true, pred, drop_intermediate=True)
    auc = metrics.auc(fpr, tpr)
    return i, auc

pool = mp.Pool(3) 
result = pool.map_async(roc, ((i, true[i], pred[i]) for i in range(2)))
pool.close()
pool.join()
print result.get()

Python is not supported tail call optimization, therforer, recursive call function should transform loop function.
my god!