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Prediction Results

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Prediction Input:

Fixed Acidity:

Volatile Acidity:

Citric Acid:

Residual Sugar:

Chlorides:

Free Sulfur Dioxide:

Total Sulfur Dioxide:

Density:

pH:

Sulphates:

Alcohol:

Wine Quality Prediction:

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Results Source Code Dataset

Wine Quality Prediction

Using Polynomial Regression Model

After submitting the form, wait at least 10 seconds for the model to calculate and show the result.
Also, all entered float numbers must have at most 2 decimal points, like: 1.23

Fixed Acidity (Between 3.8 and 14.2)

Volatile Acidity (Between 0.08 and 1.1)

Citric Acid (Between 0 and 1.66)

Residual Sugar (Between 0.6 and 65.8)

Chlorides (Between 0.009 and 0.346)

Free Sulfur Dioxide (Between 2 and 289)

Total Sulfur Dioxide (Between 9 and 440)

Density (Between 0.98711 and 1.03898)

pH (Between 2.72 and 3.82)

Sulphates (Between 0.22 and 1.08)

Alcohol (Between 8 and 14.2)

Submit

Model Description:

Regression is a supervised machine learning method for understanding the relationship between independent variables or features and a dependent variable or outcome. One of the algorithms used for regression is the “Polynomial Regression”.
Here, we use the Wine_Quality.csv dataset for regression purposes and you can download the dataset from the link on top of this page. This dataset has 11 features:
“fixed acidity”, “volatile acidity”, “citric acid”, “residual sugar”, “chlorides”, “free sulfur dioxide”, “total sulfur dioxide”, “density”, “pH”, “sulphates” and “alcohol”
And the prediction variable is: “Wine Quality”.
In the above form, you enter the values of 11 features and the model returns the Wine Quality in a pop-up form. Notice that the values and ranges of each feature are as below:

3.8 < Fixed Acidity < 14.2

0.08 < Volatile Acidity < 1.1

0 < Citric Acid < 1.66

0.6 < Residual Sugar < 65.8

0.009 < Chlorides < 0.346

2 < Free Sulfur Dioxide < 289

9 < Total Sulfur Dioxide < 440

0.98711 < Density < 1.03898

2.72 < pH < 3.82

0.22 < Sulphates < 1.08

8 < Alcohol < 14.2

3 < Wine Quality < 9

The sample code used to train a “Polynomial Regression” model, is provided in the link on top of this page. Each time you run this form and predictions happen, the values will store in the database, and with the link “result” on top of this page, you will see the previous results of the model prediction. Your recent run will be added to the end of this list.