如何在下面这段函数中给nv值限制在nu <= 0 or nu > 1的取值范围内：# 定义适应度评价函数，使用交叉验证计算准确率 def evaluate(individual): clf.set_params(kernel='rbf', gamma=individual[0], nu=individual[1]) accuracy = 0 for i in range(5): X_train, X_test = train_test_split(X_TRAIN, test_size=0.2) clf.fit(X_train) accuracy += clf.score(X_test) return accuracy / 5,

可以使用if语句进行判断，若nu的取值不在规定范围内，则将nv的值赋为0或1。修改后的代码如下：

def f(nu):
    if nu <= 0:
        nv = 0
    elif nu > 1:
        nv = 1
    else:
        nv = nu**2
    return nv