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Classification of tweets into positive and negative using classifiers like SVM, Logistic Regression, Naive bayes. Implementation of porter stemmer algorithm.

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Name		Name	Last commit message	Last commit date
Latest commit History 42 Commits
Document		Document
output_data		output_data
src		src
README.md		README.md

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Sentiment Analysis Of Tweets

There are three folders

Document - Contains all the document part
Output - Contains graphs and final output data
src - Contains actual code of the project

Files that contain final code:

porter_stemmer.py
Naive_Bayes.ipynb
Logistic Regression.ipynb
NLTK.ipynb
SVM.ipynb
data_process_fb_amazon.ipynb
process_split_store.ipynb

Rest other file contains the code written during intermediate state and testing purpose.

By:-

Sopnesh Gandhi
Rushitkumar Jasani
Priyendu Mori
Niharika Khare

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Classification of tweets into positive and negative using classifiers like SVM, Logistic Regression, Naive bayes. Implementation of porter stemmer algorithm.

machine-learning sentiment-analysis naive-bayes-classifier logistic-regression svm-classifier porter-stemmer-algorithm knn-classification

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