伙计们，我对ML很陌生。我试图在fmri数据集上建立线性回归模型。在传递x_train、y_train代码时，它显示了以下错误

Question

import seaborn as sns
import pandas as pd
import numpy as nm
import matplotlib.pyplot as plt
        
df=sns.load_dataset('fmri')

x=df[['timepoint','subject']]
y=df['signal']

from sklearn.linear_model import LinearRegression 

from sklearn.model_selection import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_5388\1414350166.py in <module>
----> 1 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)

~\Anaconda3\envs\MACHINELEARNING\lib\site-packages\sklearn\model_selection\_split.py in train_test_split(test_size, train_size, random_state, shuffle, stratify, *arrays)
   2415         raise ValueError("At least one array required as input")
   2416 
-> 2417     arrays = indexable(*arrays)
   2418 
   2419     n_samples = _num_samples(arrays[0])

~\Anaconda3\envs\MACHINELEARNING\lib\site-packages\sklearn\utils\validation.py in indexable(*iterables)
    376 
    377     result = [_make_indexable(X) for X in iterables]
--> 378     check_consistent_length(*result)
    379     return result
    380 

~\Anaconda3\envs\MACHINELEARNING\lib\site-packages\sklearn\utils\validation.py in check_consistent_length(*arrays)
    332         raise ValueError(
    333             "Found input variables with inconsistent numbers of samples: %r"
--> 334             % [int(l) for l in lengths]
    335         )
    336 

ValueError: Found input variables with inconsistent numbers of samples: [53940, 1064]

Answer 1

除了Nick ODell在关于X未被定义的注释中所指出的，您看到的ValueError是因为在两个不同大小的数组上调用train_test_split。您对train_test_split的X和y输入需要相同的大小，这里分别是53940和1064。换句话说，对于每一个输入，您都需要一个输出。hth。

Answer 2

是的，请检查xin x=df[['timepoint','subject']]和X in train_test_split(X...

然而，

df=sns.load_dataset('fmri')

这应该是

df=pd.read_csv('fmri') # but I don't know the format for this data set

只需确保脚本在与fmri相同的目录下运行

一个小的示例数据集将是很酷的。您正在使用sns和matplotlib进行绘图，但是ins不会加载一个数据集，即pandas