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The reviews from different e-commerce websites are analysed through different classification techniques namely Naive Bayes, k nearest neighbor and SVMs

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aadishjain2212/reviews-sentiment-classifier

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reviews-sentiment-classifier

The reviews from different e-commerce websites are analysed through different classification techniques namely Naive Bayes, k nearest neighbor and SVMs

getting started

1.Clone the repository.
2.unzip the downloaded zip file to get three files
a.sentiment_classifier.py
b.reviews.txt(this contains the reviews retrived from different websites i.e. our training set ) c.NumberOfPosandNeg.py
3. Run the sentiment_classifier.py
-this will create dataset.csv to store our training set
4. now run the NumberOfPosandNeg.py file to get the graph.

pre requisites

these libraries should be pre installed before running the code
1.nltk
2.sklearn
3.numpy
4.matplotlib

built-with

python

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The reviews from different e-commerce websites are analysed through different classification techniques namely Naive Bayes, k nearest neighbor and SVMs

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