Analysis, Exploration and Prediction on Wine data
Data Exploration with Wines You have access, in this folder, to two datasets of wines' characteristics.
In the Training Dataset, each wine is described by 13 features. Please pay special attention to two of them:
● Color: Here you have a categorical feature, with "R" meaning red wine and "W" meaning white wine.
● Quality: An integer number which represents the quality of the wine, as judged by experts. Higher numbers means greater quality.
All other features are real positive numbers.
In the Test Dataset, you have more wines, but this time without three of those features: density, color and quality.
You are asked to build a method to predict the values of those three features for each wine of the Test Dataset - generate a file "answer.csv" with the wines of the Test Dataset and three more columns (density, color and quality) which are your predictions for each feature.
We are more interested about the methodology you used to approach this problem than the results themselves. Bonus for readable and well-organized scripts (that doesn't mean you need to leave comments everywhere, though)!