Medicine Review with Sentiment Analysis - ML

Category: Artificial Intelligence

Sentiment Analysis on medicine reviews:

- Data pre-processing (feature extraction, removing stop words, punctuations, stemming, lemmatization etc.).
- Run models.
- Conclude and visualize data (accuracy, confusion matrix etc.).

Binary Class:

Accuracy:

Naive Bayes : 53 %

Adaboost : 89 %

Logistic Regression : 80 %

CatBoost : 90.7 %

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Multi-class (5-classes):

Class Count:

Class	Effectiveness	Count
0	Highly Effective	1741
1	Considerably Effective	1238
2	Moderately Effective	572
3	Ineffective	329
4	Marginally Effective	263

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Accuracy:

Naive Bayes : 34 %

Adaboost : 44 %

Logistic Regression : 48 %

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