wine-quality-predition---classification

cl;asification problem using classification models in supervised learning

Wine Quality Prediction Analysis - Classification

Dataset Information

The two datasets are related to red and white variants of the Portuguese "Vinho Verde" wine. These datasets can be viewed as classification or regression tasks. The classes are ordered and not balanced (e.g. there are munch more normal wines than excellent or poor ones). Outlier detection algorithms could be used to detect the few excellent or poor wines. Also, we are not sure if all input variables are relevant. So it could be interesting to test feature selection methods. Two datasets were combined and few values were randomly removed.

Attribute Information:

Input variables (based on physicochemical tests):
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 variable (based on sensory data):
12 - quality (score between 0 and 10)

Download link: https://www.kaggle.com/rajyellow46/wine-quality

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