A logistic regression model is developed to explore the quality of wine
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A logistic regression model is developed to explore the quality of wine

6. A logistic regression model is developed to explore the quality of wine on several different variables. The explanation of variables can be found here. The rating of wine is ranged from 0 to 10. In this model, we consider the wine as good quality if the rating is more than six. Otherwise, we regard it as poor quality. Consider the following as the screenshot of R-studio analysis.

6.1. Write the logistic regression equation. Interpret the model.

6.2. What is the quality of the wine with the following characteristics?

• fixed acidity=7

• volatile acidity=0.3

• citric acid=0.4

• residual sugar=11

• chlorides=0.05

• free sulfur dioxide=37

• total sulfur dioxide=188

• density=0.99

• PH=3.2

• sulphates=0.44

• alcohol=11

Hint
Management6.1) One of the most often used Machine Learning algorithms, within the category of Supervised Learning, is logistic regression. Using a predetermined set of independent factors, it is used to predict the categorical dependent variable. A categorical dependent variable's output is predicted by logistic regression. Equation for Logistic Regression: Y is the dependent variable (the variabl...

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