使用LinearRegression进行预测时出现ValueError

Question

我已经开始学习ML。

这是我的代码：

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd

# Import the dataset
dataset = pd.read_csv('Salary_Data.csv')
X = dataset.iloc[:, :-1].values
Y = dataset.iloc[:, 1].values


# Split the data set into Training Set and Test Set
from sklearn.model_selection import train_test_split
X_train, X_test, Y_train, Y_test =\
   train_test_split(X, Y, test_size=1/3, random_state=0)

# Feature Scaling
from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler()
X_train = sc_X.fit_transform(X_train)
X_test = sc_X.transform(X_test)

# Fitting Simple Linear Regression to Training Set
from sklearn.linear_model import LinearRegression
regressor = LinearRegression()
regressor.fit(X_train , Y_train)


# Predicting the Test set Results
y_pred = regressor.predict(X_test)

我遇到了错误：

ValueError：找到的数组包含0个样本（shape =（0，1）），而a 至少需要1个。

最后一行。如何解决这个问题？