GitHub - DohaoSTR/kinopoisk-reviews-sentiment-analysis: 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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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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Name		Name	Last commit message	Last commit date
Latest commit History 7 Commits
.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).