RubixML/Sentiment
An example project using a feed-forward neural network for text sentiment classification trained with 25,000 movie reviews from the IMDB website.
This tool helps you automatically determine if a piece of English text expresses a positive or negative sentiment. You input any English text, and it outputs a classification of either "positive" or "negative." This is ideal for anyone who needs to quickly gauge public opinion or emotional tone from written content, such as a market researcher, social media analyst, or content moderator.
115 stars. No commits in the last 6 months.
Use this if you need to classify the sentiment of English text as either positive or negative using a pre-trained machine learning model.
Not ideal if you need to detect nuanced emotions (like anger or joy), classify sentiment in languages other than English, or require a very fast setup without specific technical requirements.
Stars
115
Forks
14
Language
PHP
License
MIT
Category
Last pushed
Jul 25, 2025
Commits (30d)
0
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