:notebook: Long(er) text representation and classification using Doc2Vec embeddings
Text classification model which uses gensim Doc2Vec for generating paragraph embeddings and scikit-learn Logistic Regression for classification.
25,000 IMDB movie reviews, specially selected for sentiment analysis. The sentiment of reviews is binary (1 for postive, 0 for negative).
This source dataset was collected in association with the following publication:
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. (2011). "Learning Word Vectors for Sentiment Analysis." The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011).
Install the required tools
pip install -r requirements.txt
Run the script
python text_classifier.py