This project is about the prediction of red wine quality using different machine learning algorithms

These datasets can be viewed as classification or regression tasks. The classes are ordered and not balanced (e.g. there are much more normal wines than excellent or poor ones).

This repository stored the output of IBM SPSS's multiple linear regression and factor analysis of red wine quality dataset. The dataset used is from Kaggle (https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009). The software used in this repository is IBM SPSS 26