# Algorithm best compare similarities between two data sets in percentage

I'm trying to create an algorithm that finds the percentage of similarity between two subjects with sets of survey questions.

Example:

Q1: Do you prefer physically demanding tasks? A1: Nope Maybe Yes --> Subject_1 Choose Maybe / Subject_2 choose Yes

Q1: Do you prefer the outdoors? A1: Nope Maybe Yes --> Subject_1 Choose Yes / Subject_2 choose Yes

from this data, we are able to see the likey percentage they match.

Forgive me I'm new. Thank you in advance.

What you make of that will depend on your use case. If you can expect your users to understand what these values mean you can use them as they are; if you want just a quick and easily understood score (like in those online "How much of an X are you?" tests), it may make sense to just stretch the scale and clip to 0%. (I.e. take the distance $$d$$, calculate $$sim = (1 - 3 \times d) \times 100%$$ and show any negative values as "0% match", where the factor 3 depends on the size of your questionnaire and the diversity of the answers). That won't be a highly scientific metric, but then again, "percent match" often are not.