我用线性回归的简单预测不会执行

Question

以下是我的试用代码：

from sklearn import linear_model

# plt.title("Time-independent variant student performance analysis")

x_train = [5, 9, 33, 25, 4]
y_train = [35, 2, 14 ,9, 7]
x_test = [14, 2, 8, 1, 11]

# create linear regression object
linear = linear_model.LinearRegression()

#train the model using the training sets and check score
linear.fit(x_train, y_train)
linear.score(x_train, y_train)

# predict output
predicted = linear.predict(x_test)

运行时，这是输出：

  

ValueError：找到样本数不一致的数组：[1 5]

Answer 1

重新定义

x_train = [[5],[9],[33],[25],[4]]
y_train = [35,2,14,9,7]
x_test = [[14],[2],[8],[1],[11]]

来自fit(X, y)的文档：X：numpy数组或形状稀疏矩阵[n_samples,n_features]

在您的情况下，每个示例只有一个功能。