Rakesh9100/ML-Project-Drug-Review-Dataset
This is an innovative machine learning project that utilizes patient reviews with many other attributes to analyze and evaluate the effectiveness of drugs.
Combines NLP text vectorization (TfidfVectorizer) with structured feature engineering to transform patient reviews into predictive signals for drug ratings. The pipeline preprocesses temporal data, handles missing values via SimpleImputer, and encodes categorical attributes before training multiple scikit-learn classifiers for comparative performance evaluation. Built on the UCI Drug Review Dataset (Drugs.com), it leverages pandas, BeautifulSoup, and matplotlib for end-to-end data processing, modeling, and visualization.
102 stars. No commits in the last 6 months.
Stars
102
Forks
121
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 02, 2025
Commits (30d)
0
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