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Sentiment analysis of kinopoisk (https://www.kinopoisk.ru/) reviews. For analysis i used: classification methods (random forest, svc, k-neighbors) neural networks (lstm, mlp).

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DohaoSTR/kinopoisk-reviews-sentiment-analysis

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.gitignore

.gitignore

 
 

.info

.info

 
 

cleaned_dataset.xlsx

cleaned_dataset.xlsx

 
 

data_processing.py

data_processing.py

 
 

dataset.xlsx

dataset.xlsx

 
 

get_data_from_files.py

get_data_from_files.py

 
 

get_review_sentiment.py

get_review_sentiment.py

 
 

get_selection_dictionary.py

get_selection_dictionary.py

 
 

k_neighbors.py

k_neighbors.py

 
 

model_training.py

model_training.py

 
 

random_forest.py

random_forest.py

 
 

svc.py

svc.py

 
 

tensor_lstm.py

tensor_lstm.py

 
 

tensor_mlp.py

tensor_mlp.py

 
 

vectorize_data.py

vectorize_data.py

 
 

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Sentiment analysis of kinopoisk (https://www.kinopoisk.ru/) reviews. For analysis i used: classification methods (random forest, svc, k-neighbors) neural networks (lstm, mlp).

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data-science data-mining sentiment-analysis neural-network tensorflow scikit-learn lstm classification mlp sentiment-classification vectorized random-forest-classifier svc-svm
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