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Wine Quality Analysis and Prediction by Gaurav Rajula is a document available to read on EtoBox.

What is Wine Quality Analysis and Prediction about?

The document outlines a data analysis project on the Wine Quality dataset, detailing the importation of necessary libraries, data preprocessing, and exploratory data analysis. Key findings include the most frequent wine quality, correlations between various features and wine quality, and the training of Decision Tree and Random Forest models to predict wine quality with accuracy scores of 0.675 and 0.725, respectively. The Random Forest model outperformed the Decision Tree model in terms of accuracy.

Author

Gaurav Rajula

Language

EN