import pandas as pd from sklearn.linear_model import LinearRegression # 读取数据表 data = pd.read_excel('D://数据1.xlsx', sheet_name='4') # 将数据表分为X和y两部分,其中X为前三列数据,y为最后一列数据 X = data.iloc[:, :4] y = data.iloc[-1, :] # 拟合线性回归模型 model = LinearRegression() model.fit(X, y) # 预测每一列的预测值 y_pred = model.predict(X) # 输出每一列的预测值 print(y_pred)出现Traceback (most recent call last): File "D:\anaconda\lib\site-packages\IPython\core\interactiveshell.py", line 3460, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-2-1c2c07b8ba7f>", line 1, in <module> runfile('D:\\Users\\Admin\\PycharmProjects\\pythonProject2\\线性预测8.py', wdir='D:\\Users\\Admin\\PycharmProjects\\pythonProject2') File "D:\PyCharm 2023.1.1\plugins\python\helpers\pydev\_pydev_bundle\pydev_umd.py", line 198, in runfile pydev_imports.execfile(filename, global_vars, local_vars) # execute the script File "D:\PyCharm 2023.1.1\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "D:\Users\Admin\PycharmProjects\pythonProject2\线性预测8.py", line 13, in <module> model.fit(X, y) File "D:\anaconda\lib\site-packages\sklearn\linear_model\_base.py", line 648, in fit X, y = self._validate_data( File "D:\anaconda\lib\site-packages\sklearn\base.py", line 565, in _validate_data X, y = check_X_y(X, y, **check_params) File "D:\anaconda\lib\site-packages\sklearn\utils\validation.py", line 1124, in check_X_y check_consistent_length(X, y) File "D:\anaconda\lib\site-packages\sklearn\utils\validation.py", line 397, in check_consistent_length raise ValueError( ValueError: Found input variables with inconsistent numbers of samples: [1258, 4]错误
时间: 2023-06-30 07:15:51 浏览: 214
LDA.zip_lda_机器学习 LDA判别_线性判别分析_西瓜python_西瓜数据集
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出现这个错误是因为你的 `y` 只有一行数据,而 `X` 有多行数据,导致无法进行线性回归模型的拟合。你应该将 `y` 改为一个一维数组或者一个DataFrame,例如:
```python
X = data.iloc[:, :4]
y = data.iloc[-1, :].values.reshape(-1, 1) # 将y转换成一个二维数组
model = LinearRegression()
model.fit(X, y)
y_pred = model.predict(X)
print(y_pred)
```
这样就可以避免这个错误了。请注意,我们将 `y` 转换成了一个二维数组,这是因为 `sklearn` 库中的线性回归模型要求 `y` 必须是一个二维数组。如果 `y` 是一个一维数组,需要使用 `reshape` 方法将其转换成一个二维数组。
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