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OneHot+NB.ipynb

OneHot+NB.ipynb

 
 

Paper_LightWeightedSAModel.pdf

Paper_LightWeightedSAModel.pdf

 
 

QingHao.py

QingHao.py

 
 

README.md

README.md

 
 

TFIDF+FCNN(Best Model).ipynb

TFIDF+FCNN(Best Model).ipynb

 
 

W2V(tensor)+SVM.ipynb

W2V(tensor)+SVM.ipynb

 
 

W2V+FCNN.ipynb

W2V+FCNN.ipynb

 
 

W2V+SVM.ipynb

W2V+SVM.ipynb

 
 

W2Vtensor.ipynb

W2Vtensor.ipynb

 
 

data_preprocessing.ipynb

data_preprocessing.ipynb

 
 

integrated_model.ipynb

integrated_model.ipynb

 
 

pre_slides.pdf

pre_slides.pdf

 
 

tfidf_w2v.ipynb

tfidf_w2v.ipynb

 
 

w2v.ipynb

w2v.ipynb

 
 

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Light weight Sentiment Analysis Model

[Machine Learning Final Project]

Main Conrtibutions

  • By adopting TFIDF followed with a very basic FCNN classifer, we reach the accuracy(91%) comparable to BERT/LSTM on small datasets.

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