AUC曲线绘制在python

我对SVM AUC Python代码疑问：AUC曲线绘制在python

print(__doc__) 

import numpy as np 
import matplotlib.pyplot as plt 
from sklearn import svm, datasets 
from sklearn.metrics import roc_curve, auc 
from sklearn.cross_validation import train_test_split 
from sklearn.preprocessing import label_binarize 
from sklearn.svm import SVC 
from sklearn.multiclass import OneVsRestClassifier 



from sklearn.feature_extraction.text import TfidfVectorizer 
import numpy as np 
tfidf_vect= TfidfVectorizer(use_idf=True, smooth_idf=True, sublinear_tf=False, ngram_range=(2,2)) 
from sklearn.cross_validation import train_test_split, cross_val_score 

import pandas as pd 

df = pd.read_csv('merged_quantized_list.csv', 
        header=0, sep=',', names=['id', 'content', 'label']) 


X = tfidf_vect.fit_transform(df['content'].values) 
y = df['label'].values

首先怀疑的是，因为我的CSV文件包含60列和5000行，其中第一行是我的标签和休息是内容。这个x和y是否包含内容和标签？

第二件事是：当我运行这段代码，我得到了错误：

X = tfidf_vect.fit_transform(df['content'].values) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/sklearn/feature_extraction/text.py", line 1352, in fit_transform 
    X = super(TfidfVectorizer, self).fit_transform(raw_documents) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/sklearn/feature_extraction/text.py", line 839, in fit_transform 
    self.fixed_vocabulary_) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/sklearn/feature_extraction/text.py", line 762, in _count_vocab 
    for feature in analyze(doc): 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/sklearn/feature_extraction/text.py", line 241, in <lambda> 
    tokenize(preprocess(self.decode(doc))), stop_words) 
    File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/sklearn/feature_extraction/text.py", line 207, in <lambda> 
    return lambda x: strip_accents(x.lower()) 
AttributeError: 'numpy.int64' object has no attribute 'lower'

请帮助我。在此先感谢

来源

2017-04-10 Dhara

对不起，我的CSV文件包含60个colomns和5000行，其中第一colomn是 – Dhara

是否“内容”一栏只包含任何整数或字符串的标签？这个错误是因为在提供的数据中有整数，所以'lower（）'（小写字符串）不能应用于它。 –

尝试：

X = tfidf_vect.fit_transform(df['content'].values.astype(str))

来源

2017-04-10 15:49:01

AUC曲线绘制在python

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