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@joshua040404 joshua040404 released this 16 Dec 02:17
final_submission
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This release contains the completed implementation of the Wine Quality Prediction project, developed in Rust. The project uses the Wine Quality Dataset from the UC Irvine Machine Learning Repository to predict wine quality based on various chemical properties.

Key features of this release:

  1. Data Cleaning: Implemented feature normalization and handling of missing values.
  2. Exploratory Data Analysis: Computed key statistics and compared red and white wine characteristics.
  3. Feature Importance Analysis: Determined the most influential features for wine quality prediction.
  4. Predictive Modeling: Built a logistic regression model to classify wine quality.
  5. Testing: Added unit tests to verify the functionality of core components.
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