weighted_Fscore.py

weighted_Fscore.py

def weighted_Fscore(y_true, y_pred):
    Beta_1 = 0.5
    Beta_2 = 0.125
    Beta_3 = 0.125
    N_tu = 0
    N_td = 0
    N_tf = 0
    
    E_wutd = 0
    E_wdtu = 0
    E_wutf = 0
    E_wdtf = 0
    E_wftu = 0
    E_wftd = 0

    assert(len(y_true) == len(y_pred)), "len(y_true) 不等於 len(y_pred)"
    
    for i in range(len(y_true)):
        true = y_true[i]
        pred = y_pred[i]
        if true == 0:
            if pred ==0:
                N_tf+=1
            elif pred==1:
                E_wutf+=1
            elif pred==2:
                E_wdtf+=1
                
        elif true == 1:
            if pred ==0:
                E_wftu+=1
            elif pred==1:
                N_tu+=1
            elif pred==2:
                E_wdtu+=1
                
        elif true == 2:
            if pred ==0:
                E_wftd+=1
            elif pred==1:
                E_wutd+=1
            elif pred==2:
                N_td+=1
    
    N_tp = N_tu + N_td + (Beta_3*Beta_3)*N_tf
    E_1st = E_wutd + E_wdtu
    E_2nd = E_wutf + E_wdtf
    E_3rd = E_wutf + E_wftd
    
    print(N_tp, N_tu, N_td, N_tf)
    print(E_1st , E_wutd , E_wdtu)
    print(E_2nd , E_wutf , E_wdtf)
    print(E_3rd , E_wftu , E_wftd)

    return (1+ Beta_1*Beta_1 + Beta_2*Beta_2 )*N_tp / ((1+ Beta_1*Beta_1 + Beta_2*Beta_2 )*N_tp + E_1st + Beta_1*Beta_1*E_2nd + Beta_2*Beta_2*E_3rd)