I have a continuous target variable named "quality" which ranges from 0 to 10. Also I have 11 input variables in my dataset.
When I'm building my model using DecisionTreeClassifier() of sklearn then I'm getting a score of 60% but when I'm building my model using DecisionTreeRegressor() of sklearn then I'm getting accuracy of 3% only and also RMSE as 85%.
Also, when using Linear Regression my R-squared value is 0.376. Is it good?
Dataset Link : https://archive.ics.uci.edu/ml/datasets/Wine+Quality
Am I doing something wrong?
I need help. Thank you.