Classification or Regression approach?

Hi everyone. I have a dataset with 13 chemical characteristics of a product (food) and a target variable named quality that is a score in a scale of 1 to 10 (integers only) given by people who taste the product. I want to see if it is possible to train a model to classify the quality of the product given his chemical properties. My doubt is: should I go with Random Forest classifier or Regression? Should I go with Support Vector Machine or Regressor? Since this 1 to 10 scale seems a bit subjective to me (based on personal preference and taste only) I am not sure this is a true numeric scale. A product with score 6 worth double of a product with score 3? Don’t think so… can you please give me your opinions and possible literature on this? Thank you