CMPE-256-Project - Sentiment analysis on Hotel reviews

Instruction to run the code

Python should be installed on your operating system (Anaconda2 Recommended).
Make sure you have sklearn, pandas, numpy, matplotlib, scipy, wordcloud, nltk packages installed.
Download the english stopwords from nltk.
Make sure “deceptive-opinion.csv” file are present in the same directory of the source code.
Run the code using jupyter Notebook or any other interactive python command shell.

svm-FinalProject is the our final project code which has the highest F1 score.

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
.ipynb_checkpoints		.ipynb_checkpoints
.DS_Store		.DS_Store
CMP-256-ProjectReport.pdf		CMP-256-ProjectReport.pdf
NaiveBayesClassifier.ipynb		NaiveBayesClassifier.ipynb
README.md		README.md
Random+Forest.ipynb		Random+Forest.ipynb
SVM_Postive_Negative.ipynb		SVM_Postive_Negative.ipynb
SVM_Truthful_Deceptive.ipynb		SVM_Truthful_Deceptive.ipynb
svm-finalProject.ipynb		svm-finalProject.ipynb