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Python/Sklearn-索引器错误-索引超出界限

scikit-learn pandas python

0xgareth · 技术社区 · 7 年前

下面是我的代码

filename = 'train4.csv'
names = ['attribut names are here']
dataframe = read_csv(filename, names=names)
array = dataframe.values
X = array[:,0:47]
Y = array[:,47]
num_folds = 10
kfold = KFold(n_splits=10, random_state=7)
model = KNeighborsClassifier()
results = cross_val_score(model, X, Y, cv=kfold)
print(results.mean())

我得到了错误

>IndexError                                Traceback (most recent call last)
<ipython-input-19-8d9596c3368b> in <module>()
      4 array = dataframe.values
      5 X = array[:,0:47]
----> 6 Y = array[:,47]
      7 num_folds = 10
      8 kfold = KFold(n_splits=10, random_state=7)

> IndexError: index 47 is out of bounds for axis 1 with size 47

在我的CSV中,第47个属性是目标标签-因此是48(我错了吗?)。

我正在Jupyter笔记本上运行pandas/sklearn。

谢谢

1 回复 | 直到 7 年前

MaxU - stand with Ukraine 7 年前

试试这个:

import pandas as pd

filename = 'train4.csv'
names = ['attribut names are here']
target_col_name = 'name_of_your_target_column'

df = pd.read_csv(filename, names=names)

num_folds = 10
kfold = KFold(n_splits=10, random_state=7)
model = KNeighborsClassifier()
results = cross_val_score(model,
                          df.drop(target_col_name, axis=1), 
                          df[target_col_name],
                          cv=kfold)
print(results.mean())

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