AmirhosseinHonardoust/Sentiment-Analysis-NLP
Customer reviews sentiment analysis with Python and NLP. Generates a synthetic dataset of positive, neutral, and negative reviews, applies preprocessing (tokenization, stopwords, lemmatization), and builds TF-IDF features. Trains classifiers (Naive Bayes, Logistic Regression, Random Forest) with evaluation, confusion matrix and top features.
Includes unigram+bigram TF-IDF vectorization and model persistence via joblib for deployment. Generates comparative metrics across three classifiers with macro F1-score-based selection, while producing interpretability artifacts (word clouds, per-class feature rankings) alongside standard evaluation metrics and classification reports.
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27
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Language
Python
License
MIT
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Last pushed
Sep 11, 2025
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