Question

我将sklearn与numpy数组配合使用。我有2个数组（x，y），它们应该是：

test_size=0.2
train_size=0.8

这是我当前的代码：

def predict():

    sample_data = pd.read_csv("includes\\csv.csv")

    x = np.array(sample_data["day"])
    y = np.array(sample_data["balance"])


    x = x.reshape(1, -1)



    y = y.reshape(1, -1)




    print(x)
    print(y)



    X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.2)



    clf = LinearRegression()
    clf.fit(x_train, y_train)

    clf.score(x_test, y_test)

错误是：

ValueError: With n_samples=1, test_size=0.2 and train_size=None, the resulting train set will be empty. Adjust any of the aforementioned parameters.

，它出现在行中：

X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.2)

为什么会出现任何想法？

Answer 1

我有这个问题。检查库“ scikit-learn”。 sklearn与scikt-learn的0.20.0+版本有关，请尝试这样做：

Windows：pip uninstall scikit-learn
Linux：sudo python36 -m pip uninstall scikit-learn

并安装：

Windows：pip install scikit-learn==0.19.1
Linux：sudo python36 -m pip install scikit-learn==0.19.1

如何在Python Numpy中使用train_test_split修复Value Error

1 个答案: