https://github.com/jetsemrick/aml_phrase_sentiment

Applied machine learning project for movie review sentiment analysis.
https://github.com/jetsemrick/aml_phrase_sentiment

Last synced: 6 days ago
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Applied machine learning project for movie review sentiment analysis.

• Host: GitHub
• URL: https://github.com/jetsemrick/aml_phrase_sentiment
• Owner: jetsemrick
• Created: 2024-10-28T19:42:50.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-11-04T19:57:37.000Z (2 months ago)
• Last Synced: 2024-11-12T01:23:39.695Z (2 months ago)
• Language: Python
• Homepage:
• Size: 5.15 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## Applied Machine Learning Phrase Sentiment Prediction

### Overview

This project is based on data from the Rotten Tomatoes movie review dataset. Our goal is to model the relationship between phrases in movie reviews and the sentiment score. We tested different supervised and unsupervised methods to determine what strategy produces the most accurate model.

### Dataset

The data is a mixture of labeled and unlabeled phrases from movie reviews. Each phrase has a sentiment [0,1,2,3,4] or is unlabeled [-100].

### Models

- Logistic Regression

- K Nearest Neighbor (KNN)

- Gaussian Mixture (GMM)

- K-means Clustering

### Intrstructions

To build and test each model, download all dependencies and execute main.py