Computer and Technology Dataset Guide

Understanding wine quality dataset and how it is used in machine learning

Here in this guide, let’s try and predict the very quality of the wine based on the given features. The dataset has the key features that are very much responsible for influencing the quality of a wine. Here we’ll only deal with a white kind of wine quality; the classification technique is used to check further the very quality of bad or good wine. 

The dataset description:

Well, in the dataset, the classes are generally ordered. However, it wasn’t balanced. Here, the red wine cases are higher, and the white wine instance is less than the red.

Listed below are the names of attributes from a dataset -:

  1. The type
  2. The fixed acidity
  3. The volatile acidity
  4. The citric acid
  5. The residual sugar
  6. The chlorides
  7. Free Sulfur dioxide
  8. The total sulfur dioxide
  9. The density
  10. The ph
  11. The sulphates
  12. The alcohol
  13. The quality

Preparing datasets for machine learning projects feature variables

At this point, one will felt that he’s ready to go on and prepare datasets for machine learning projects. The very first thing, one would go on to standardize the data. Standardizing data usually means that it’ll go on to transform data so that the distribution will likely have a mean of zero and the standard deviation- 1. 

It is crucial to standardize the data to equalize the series of data. For instance, imagine the dataset with a couple of input features: the height in mm and the weight in terms of pounds. Because values of the ‘height’ are much higher because of its measurement, the greater stress will be placed automatically on height when compared to weight, making a bias.

Linda Alvarado loves writing about technology and science updates. She also loves to keep her mind and body fresh by doing intense workouts and meditation sessions.