我用线性回归简单的预测不会执行

Question

下面是我的审判代码：

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: Found arrays with inconsistent numbers of samples: [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]] 

从DOC fit(X, y)：X：numpy数组或形状的稀疏矩阵[n_samples,n_features]

就你而言，每个例子只有一个功能。