| license: mit | |
| language: | |
| - en | |
| metrics: | |
| - accuracy | |
| library_name: sklearn | |
| pipeline_tag: text-classification | |
| tags: | |
| - code | |
| ## Model Training | |
| The sentiment analysis model is trained using a Support Vector Machine (SVM) classifier with a linear kernel. The cleaned text data is transformed into a bag-of-words representation using the CountVectorizer. The trained model is saved as `Sentiment_classifier_model.joblib`, and the corresponding TF-IDF vectorizer is saved as `vectorizer_model.joblib`. | |