solution.py 文件源码

def selectThreshold(yval,pval):
    '''???????'''
    bestEpsilon = 0.
    bestF1 = 0.
    F1 = 0.
    step = (np.max(pval)-np.min(pval))/1000
    '''??'''
    for epsilon in np.arange(np.min(pval),np.max(pval),step):
        cvPrecision = pval<epsilon
        tp = np.sum((cvPrecision == 1) & (yval == 1)).astype(float)  # sum???int???????float
        fp = np.sum((cvPrecision == 1) & (yval == 0)).astype(float)
        fn = np.sum((cvPrecision == 1) & (yval == 0)).astype(float)
        precision = tp/(tp+fp)  # ???
        recision = tp/(tp+fn)   # ???
        F1 = (2*precision*recision)/(precision+recision)  # F1Score????
        if F1 > bestF1:  # ?????F1 Score
            bestF1 = F1
            bestEpsilon = epsilon
    return bestEpsilon,bestF1



# ???