I am wondering if there exists such a method in machine learning that:
Given a binary classification problem, for each person in the test set the person that most closely resembles this person in the training set acts as a donor for the value; either 0 or 1.
Could someone show point me in a direction?
Note: For instance, you have the variables age, sex and income. Sex has less spread, so we might standardize this variable to make it comparable with standardized age and income. It might then be calculated which person most closely relates to each test person.