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python textblob and text classification


python textblob and text classification

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python textblob and text classification
Tag : python , By : Paul
Date : November 28 2020, 09:01 AM

Hope this helps I'm trying do build a text classification model with python and textblob, the script is runing on my server and in the future the idea is that users will be able to submit their text and it will be classified. i'm loading the training set from csv : , Ok found that pickle module is what i need :)
Training:
# -*- coding: utf-8 -*-
import pickle
from nltk.tokenize import word_tokenize
from textblob.classifiers import NaiveBayesClassifier
with open('file.csv', 'r', encoding='latin-1') as fp:
    cl = NaiveBayesClassifier(fp, format="csv")  

object = cl
file = open('classifier.pickle','wb') 
pickle.dump(object,file)
import pickle
sys.stdout = open('demo.txt',"w");
from nltk.tokenize import word_tokenize
from textblob.classifiers import NaiveBayesClassifier
cl = pickle.load( open( "classifier.pickle", "rb" ) )
print(cl.classify("text to classify"))

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Naive Bayes text classification using TextBlob: every instance predicted as negative when adding more sample size


Tag : python , By : Maplye
Date : March 29 2020, 07:55 AM
Does that help Yes, it could be that your data set is biasing your classifier. If there isn't a very strong signal to tell the classifier which class to choose, it would make sense for it to select the most prevalent class (negative in your case). Have you tried plotting the class distributions versus accuracy? Another thing to try is k-fold validation so that you are not by chance drawing a biased 80-20 training-test split.

Is there any feature of TextBlob to obtain neutral classification?


Tag : python , By : dnyaneshwar
Date : March 29 2020, 07:55 AM
help you fix your problem I am interested in building a text classifier using textBlob but from my research does not look like after you train the classifier to return neutral tags. Does anyone know a way to implement this ? Or is there a similar library which provides neutral classification ? Thank you. , I am using If else Statement for this : like
from textblob import TextBlob
from textblob.sentiments import NaiveBayesAnalyzer

blob = TextBlob(message, analyzer=NaiveBayesAnalyzer())
a = (blob.sentiment)
if a.__getattribute__("p_pos") > a.__getattribute__("p_neg"):
    tag = str(a.__getattribute__("classification"))
    sentiment = str(a.__getattribute__("p_pos"))
elif a.__getattribute__("p_pos") < a.__getattribute__("p_neg"):
    tag = str(a.__getattribute__("classification"))
    sentiment = str(a.__getattribute__("p_neg"))
else:
    tag = "N"
    sentiment = "0"

Python 2.7 and Textblob - TypeError: The `text` argument passed to `__init__(text)` must be a string, not <type 'list


Tag : python-2.7 , By : Cadu
Date : March 29 2020, 07:55 AM
With these it helps Update: Issue resolved. (see comment section below.) Ultimately, the following two lines were required to transform my .csv to unicode and utilize TextBlob: row = [cell.decode('utf-8') for cell in row], and text = ' '.join(row). , So maybe you can make change as below:
row = str([cell.encode('utf-8') for cell in row])

Python 3.5.2: from textblob import TextBlob : TypeError


Tag : python , By : user184415
Date : March 29 2020, 07:55 AM
With these it helps Resolved it. It was an issue with nltk lib. I have followed below commands and it worked.
32-bit binary installation
Install Numpy (optional): http://sourceforge.net/projects/numpy/files/NumPy/ (the version that specifies pythnon3.4)
Install NLTK: http://pypi.python.org/pypi/nltk
Install NLTK: run sudo pip install -U nltk
Install Numpy (optional): run sudo pip install -U numpy

Python Flask Application on IBM cloud/bluemix with Textblob library throwing exception - textblob.exceptions.MissingCorp


Tag : python , By : Harry Truman
Date : March 29 2020, 07:55 AM
like below fixes the issue It seems that you do not have a nltk.txt in the root directory of your deployed app. The Cloud Foundry Python buildpacks have built-in support for NLTK. The text file holds information about which corpora need to be installed during deployment.
Sample content of a nltk.txt:
wordnet averaged_perceptron_tagger brown sentence_polarity
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