evalx.py 文件源码

def eval(name,clip=False,bar=0.9):
    base = pd.read_csv('../input/stage1_solution_filtered.csv')
    base['Class'] = np.argmax(base[['class%d'%i for i in range(1,10)]].values,axis=1)
    sub = pd.read_csv(name)
    #sub = pd.merge(sub,base[['ID','Class']],on="ID",how='right')
    #print(sub.head())
    y = base['Class'].values
    yp = sub[['class%d'%i for i in range(1,10)]].values
    if clip:
        yp = np.clip(yp,(1.0-bar)/8,bar)
        yp = yp/np.sum(yp,axis=1).reshape([yp.shape[0],1])
    print(name,cross_entropy(y,yp),multiclass_log_loss(y,yp))
    for i in range(9):
        y1 = y[y==i]
        yp1 = yp[y==i]
        print(i,y1.shape,cross_entropy(y1,yp1),multiclass_log_loss(y1,yp1))