deepakgupta1/Scoring-Airbnb-Reviews
Score prediction in the categories of cleanliness, accuracy, check-in, communication, location, value (each out of 10) and overall (out of 100) based on the reviews left by customers on Airbnb.
Implements multi-stage feature engineering combining TF-IDF, CountVectorizer, and self-trained Word2Vec embeddings on cleaned review text, alongside sentiment analysis and target-encoded categorical features. Uses LightGBM regression with Bayesian hyperparameter optimization and 10-fold stratified cross-validation to handle the skewed rating distribution. Built with scikit-learn, NLTK, and Gensim on IBM Watson for cloud-based model training.
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Jan 02, 2019
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