小编NgB*_*don的帖子

如何消除进入 countvectorizer 我的代码的数字字符

cv = CountVectorizer(min_df=50, stop_words='english',max_features = 5000,analyzer='word') 


    cv_fit_addr=cv.fit_transform(data['Adj_Addr'])



 print(cv.get_feature_names())

['01', '02', '03', '04', '05', '06', '07', '08', '09', '10', '100', '1001', '1002', '1003', '1004', '1005', '1008', '101', '1010', '102', '103', '104', '105', '106', '107', '108', '109', '10f', '10th', '11', '1101', '1102', '1103', '1104', '1105', '1106', '1108', '111', '1111', '113', '114', '116', '118', '11f', '11th', '12', '120', '1201', '1202', '1203', '1204', '1206', '1208', '121', '122', '123', '125', '126', '128', '12a', '12f', '12th', '13', '1301', '1302', '1303', '1305', '1308', '132', …

我使用标签编码器将我的分类数据标记为数字数据

data['Resi'] = LabelEncoder().fit_transform(data['Resi'])

但是当我试图找到它们如何在内部使用时

list(LabelEncoder.inverse_transform(data['Resi']))

我得到以下错误

TypeError                                 Traceback (most recent call last)
<ipython-input-67-419ab6db89e2> in <module>()
----> 1 list(LabelEncoder.inverse_transform(data['Resi']))

TypeError: inverse_transform() missing 1 required positional argument: 'y'

如何解决这个问题

样本数据

Resi
IP
IP
IP
IP
IP
IE
IP
IP
IP
IP
IP
IPD
IE
IE
IP
IE
IP
IP
IP