我的代码:
import numpy as np
from pandas import read_csv
from matplotlib import pyplot as plt
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split
data = read_csv('data.csv', usecols=['col_1'])
df_x = data.iloc[:, 1:]
df_y = data.iloc[:, 0]
x_train, x_test, y_train, y_test = train_test_split(df_x, df_y, test_size=0.9, random_state=4)
nn = MLPClassifier(activation='logistic', solver='sgd', hidden_layer_sizes=(2,), random_state=1)
#nn.fit(x_train[x], y_train[x])
print(nn)
nn.fit(x_train, y_test)
pred = nn.predict(x_test)
我从 .fit()
方法中得到了标题中所示的错误,并且由于我是 ML 新手,所以对文档了解不多。
完整错误:
File "C:/NNC/Main.py", line 14, in <module>
data.target.array([])
File "C:\NNC\venv\lib\site-packages\pandas\core\generic.py", line 5179, in __getattr__
return object.__getattribute__(self, name)
AttributeError: 'DataFrame' object has no attribute 'target'
更新-:
我已经删除并更新了它,因为这是为了测试文档中找到的解决方案。我已经更新了错误
File "C:\Users\PycharmProjects\NNC\venv\lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py", line 325, in _fit
X, y = self._validate_input(X, y, incremental)
File "C:\Users\PycharmProjects\NNC\venv\lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py", line 932, in _validate_input
multi_output=True)
File "C:\Users\PycharmProjects\NNC\venv\lib\site-packages\sklearn\utils\validation.py", line 739, in check_X_y
estimator=estimator)
File "C:\Users\PycharmProjects\NNC\venv\lib\site-packages\sklearn\utils\validation.py", line 459, in check_array
dtype_orig = np.result_type(*array.dtypes)
File "<__array_function__ internals>", line 6, in result_type
ValueError: at least one array or dtype is required
进程结束,退出代码为 1
最佳答案
由于以下原因会发生此错误:
- 您的 csv 中没有
target
列。在那里检查两次你的 csv。 - 如果您有
target
列,则targer
列中有空格。 它可能是这样存在的
< target>
<target >
< target >
<target >...etc.
用于复制带有空格的列名。之后运行这段代码
data = read_csv('data.csv', usecols=['col_1'])
data.columns = data.columns.str.strip()
更新:
如果你的数据框是这样的
a b
0 1 2
1 1 2
2 1 2
3 1 2
4 1 2
当你使用 iloc 时
df_y = data.iloc[:, 0]
output -:
a
0 1
1 1
2 1
3 1
4 1
df_y = data.iloc[:, 1]
output -:
b
0 2
1 2
2 2
3 2
4 2
在您的情况下,您使用了 df_x = data.iloc[:, 1:]
。将其更正为 df_x = data.iloc[:, 1]
。了解 iloc 的工作原理
关于python - 值错误 : at least one array or dtype is required,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/59403627/