sklearn linear_model LinearRegression, ValueError: Expected 2D array, got 1D array instead

Question

我正在尝试将数据拟合到我的模型中，

这是数据

le = sklearn.preprocessing.LabelEncoder()
date = le.fit_transform(list(data["Date"]))
_open = le.fit_transform(list(data["Open"]))
high = le.fit_transform(list(data["High"]))
low = le.fit_transform(list(data["Low"]))
adj_close = le.fit_transform(list(data["Adj Close"]))
volume = le.fit_transform(list(data["Volume"]))

X = list(date)
y = list(zip(high, low, _open, adj_close, volume))

x_train, x_test, y_train, y_test = sklearn.model_selection.train_test_split(X, y, test_size=0.1)

但是当我尝试将数据拟合到如下所示的模型中时

linear = sklearn.linear_model.LinearRegression()
linear.fit(x_train, y_train)

我收到此错误

ValueError: Expected 2D array, got 1D array instead:
array=[2088  311 1839 ... 2422   64 1705].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or 
array.reshape(1, -1) if it contains a single sample.

谢谢

Answer 1

试试这个

x_train= x_train.reshape(-1, 1)
x_test = x_test.reshape(-1, 1)