我有一些电子邮件主题和性能评级，我想用它们来预测哪些主题行会表现良好。当我运行我的MultinomialNB时，我得到一个"对象没有对齐"的错误。这是代码
import pandas as pd
import numpy as np
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_bayes import MultinomialNB
input=pd.read_csv('subject_tool_input_500.csv')
input.subject[input.subject.isnull()]=' '
good=np.asarray(input.unique_open_performance>0)
subjects=input.subject
classifier = MultinomialNB()
count_vectorizer = CountVectorizer(strip_accents='unicode')
counts=count_vectorizer.fit_transform(subjects)
classifier.fit(counts,good)
classifier.predict('test subject line')
返回以下错误:
>>> classifier.predict('test subject line')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Library/Python/2.7/site-packages/sklearn/naive_bayes.py", line 63, in predict
jll = self._joint_log_likelihood(X)
File "/Library/Python/2.7/site-packages/sklearn/naive_bayes.py", line 457, in _joint_log_likelihood
return (safe_sparse_dot(X, self.feature_log_prob_.T)
File "/Library/Python/2.7/site-packages/sklearn/utils/extmath.py", line 83, in safe_sparse_dot
return np.dot(a, b)
ValueError: objects are not aligned
这是我正在处理的输入
>>> subjects
0 Thanksgiving Dinner Delivered
1 It's Not Too Late To Order for Thanksgiving
2 Stress Free Christmas Gift They'll Love
3 Save $10 On Christmas Gift Certificates - Inst...
4 Need a Last Minute Christmas Gift?
5 Give Mom Something Special!
6 Yummy Steaks For Dad - $15 Off Your Order
7 Order a romantic dinner today and get it by Va...
8 Taiyo Yuden Unveils Latest in SAW Filter and D...
9 Taiyo Yuden New Noise Reducing Ferrite Bead Ch...
10 Lithium Ion Capacitors Are Ultimate Replacemen...
11 Art Wolfe Newsletter
12 Art Wolfe Seminar Tour 2014
13 Art Wolfe Spring 2014 Newsletter
14 Day of the Dead Sale at Art Wolfe
...
8797625 Подписка на рассылку
8797626 Подписка на рассылку
8797627 Ramadan Mubarak from MFP
8797628 Ramadan Mubarak from Insaan Relief
8797629 UK Muslims! You have one new message...
8797630 Open House - 1249 Los Robles Place, Pomona CA ...
8797631 Open House - Custom Built Home by Conrad Buff ...
8797632 Open House - Custom built by Buff, Smith & Hen...
8797633 Open House - Custom Built Home by Conrad Buff ...
8797634 Open House - Custom Built Home by Conrad Buff ...
8797635 Open House - Custom Built Home by Conrad Buff ...
8797636 Open House - Buff, Smith & Hensman custom buil...
8797637 RAMADAN PROGRAMS: Dars-e-Qur'an in Rawalpindi ...
8797638 Dars-e-Qur'an by Shaykh Hammad Mahmood
8797639 Dars-e-Qur'an by Shaykh Hammad Mahmood
Name: subject, Length: 8797640, dtype: object
>>> counts
<8797640x1172387 sparse matrix of type '<type 'numpy.int64'>'
with 62516240 stored elements in Compressed Sparse Column format>
>>> good
array([ True, False, True, ..., False, True, True], dtype=bool)
我不知道为什么会这样。上周我没有使用pandas就完成了这个任务，但是我一直在尝试使用数据框架来简化我将要做的一些后续工作。
我是个白痴。我还需要获得我试图预测的主题行的计数，因此结尾应该更像这样。
subcount=count_vectorizer.transform(["this is a test subject"])
classifier.predict(subcount)
希望以后的人能看到这一点，不要再犯同样的错误。
您需要添加tf-idf矩阵，而不仅仅是计数
subcount=count_vectorizer.transform(["this is a test subject"])
tfidf = tfidf_transformer.transform(subcount)
classifier.predict(tfidf)