Question

我正在尝试找出随机森林分类任务的功能重要性。但这给了我以下错误：

'numpy.ndarray'对象没有属性'columns'

这是我的代码的一部分：

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline


# importing dataset

dataset=pd.read_csv('Churn_Modelling.csv')
X = dataset.iloc[:,3:12].values
Y = dataset.iloc[:,13].values

#spliting dataset into test set and train set

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size = 0.20)

from sklearn.ensemble import RandomForestRegressor

regressor = RandomForestRegressor(n_estimators=20, random_state=0)  
regressor.fit(X_train, y_train) 

#feature importance

feature_importances = pd.DataFrame(rf.feature_importances_,index = X_train.columns,columns=['importance']).sort_values('importance',ascending=False)

我希望这应该为我的数据集的每一列提供要素重要性得分。（注意：原始数据以CSV格式保存）

Answer 1

因此，从X_train出来的train_test_split实际上是一个numpy数组，它将永远不会有列。其次，当您从X生成dataset时返回值numpy.ndarry而不是df时要求输入值。

您需要更改行

feature_importances = pd.DataFrame(rf.feature_importances_,index = X_train.columns,columns=['importance']).sort_values('importance',ascending=False)

到

columns_ = dataset.iloc[:1, 3:12].columns

feature_importances = pd.DataFrame(rf.feature_importances_,index = columns_,columns=['importance']).sort_values('importance',ascending=False)

Answer 2

使用此：

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline


# importing dataset

dataset=pd.read_csv('Churn_Modelling.csv')
X = dataset.iloc[:,3:12].values
Y = dataset.iloc[:,13].values

#spliting dataset into test set and train set

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size = 0.20)

from sklearn.ensemble import RandomForestRegressor

regressor = RandomForestRegressor(n_estimators=20, random_state=0)  
regressor.fit(X_train, y_train) 

#feature importance

feature_importances = pd.DataFrame(regressor.feature_importances_,index = dataset.columns,columns=['importance']).sort_values('importance',ascending=False)

Answer 3

iloc和loc函数只能应用于熊猫数据框。您正在将它们应用到数组中。解：将数组转换为数据框，然后应用iloc或loc

'numpy.ndarray'对象没有属性'columns'

3 个答案: