vrunm/Text-Classification-Financial-Phrase-Bank
Built a sentiment analysis model to predict the sentiment of a Financial News article. A comparative study of different optimizers used for training was done.
This project helps financial professionals quickly understand the sentiment of financial news. By inputting English financial news headlines, it outputs a classification of the sentiment (positive, neutral, or negative). This is useful for financial analysts, traders, or anyone needing to gauge market sentiment from news.
No commits in the last 6 months.
Use this if you need to automatically categorize the sentiment of financial news headlines with high accuracy.
Not ideal if you need to analyze sentiment for non-financial text or require in-depth, nuanced sentiment analysis beyond simple classification.
Stars
31
Forks
4
Language
Python
License
—
Category
Last pushed
Dec 01, 2023
Commits (30d)
0
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