Question

我正在使用sklearn和熊猫来创建和拟合线性回归分类器以继续图表。

我用来创建数组的代码是：

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

X_train= np.array(sample_data["day"])
y_train= np.array(sample_data["balance"])

X_test= np.array(sample_datat["day"])
y_test= np.array(sample_datat["balance"])


X_train = X_train.reshape(1, -1)
y_train = y_train.reshape(1, -1)


X_test = X_test.reshape(1, -1)
y_test = y_test.reshape(1, -1)

#plt.plot(X_train, y_train)
#plt.show()
clf = LinearRegression()
clf.fit(X_train, y_train)
clf.score(X_test, y_test)

正在打开的csv文件为：

balance,day

242537,28.5
246362,29.5
246659,30.5
246844,31.5

并且：

246987,1.6
247230,2.6

错误消息就像标题中一样：

Traceback (most recent call last):
  File "main.py", line 140, in <module>
    predict()
  File "main.py", line 59, in predict
    clf.score(X_test, y_test)
  File "C:\Users\simon\AppData\Local\Programs\Python\Python37-32\lib\site-packages\sklearn\base.py", line 408, in score
    y_pred = self.predict(X)
  File "C:\Users\simon\AppData\Local\Programs\Python\Python37-32\lib\site-packages\sklearn\linear_model\base.py", line 221, in predict
    return self._decision_function(X)
  File "C:\Users\simon\AppData\Local\Programs\Python\Python37-32\lib\site-packages\sklearn\linear_model\base.py", line 206, in _decision_function
    dense_output=True) + self.intercept_
  File "C:\Users\simon\AppData\Local\Programs\Python\Python37-32\lib\site-packages\sklearn\utils\extmath.py", line 142, in safe_sparse_dot
    return np.dot(a, b)
ValueError: shapes (1,2) and (4,4) not aligned: 2 (dim 1) != 4 (dim 0)

Answer 1

您应该将其重塑为（-1,1）而不是（1，-1）

修复ValueError：形状（1,2）和（4,4）不对齐：2（dim 1）！= 4（dim 0）在python中

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