emilbiju/Classification_Wine_Dataset

This is a project aimed at building machine learning models for classification of the wine dataset. Various machine learning models are used and fine-tuned to obtain desirable results for both binary and multi-class classification

Wine Dataset Classification

The objective of this project is to build machine learining models to predict parameters in the wine dataset. The dataset is divided into 2 parts - one containing details of various red wine samples and the other containing white wine samples.

In the first part of the project, we take up a binary classification problem and try to predict the type of wine. In the second part, we attempt to make a multiclass classification of the wine quality. The dataset contains wine quality ratings from 3 to 9 and our challenge is to predict these on a test set.

We explore the data, study trends, preprocess it and then use models like Random Forest Classification, XGBoost and Neural networks. We fine-tune the models to achieve better performance.