Wine analysis and prediction.

• This project analyzes wine data and builds a simple predictive model for wine quality.

  Input variables:

  1. fixed acidity
  2. volatile acidity
  3. citric acid
  4. residual sugar
  5. chlorides
  6. free sulfur dioxide
  7. total sulfur dioxide
  8. density
  9. pH
  10. sulphates
  11. alcohol

  Output:

  • Quality

Some featrues of the project :

• 5 models have been used to see what would give the best result, and the best has been used to predict the outcome from the user inputs.
• a column "avg total so2 and free so2" has been introduced to predict the missing value of quality, and the column has been deleted as it was not one of criteria on which the quality of the wine would be predicted.
• a dataframe has been created to list the all models created with their accuracies.

Project collaborators :

1. Vedanshi Vaghela
2. Lakshmanan S
3. Maneesh R
4. Somisetti Sridhar
5. Irugu Sindhu
6. P. Nutan karteek