I am working on building a scoring algorithm for student data,
say the attributes are :
name, location, age, class, school_name, skill1, skill2, skill3
based on these data I need to create a student score.
I need to assign weight-ages for age, class, school_name skills and come up with a score for student.
say I have 2 scoring models like :
score_1 = x1*location_weight + x2*age_weight + x2*class_weight + x3*school_name_weight + x4*skill1_weight + x5*skill2_weight + x6*skill3_weight score_2 = y1*location_weight + y2*age_weight + y2*class_weight + y3*school_name_weight + y4*skill1_weight + y5*skill2_weight + y6*skill3_weight
now how can I compare these models and evaluate them?
The problem is I don't have a test or validation set to prove or compare how accurate each of these model is, so in this case what is the best approach to compare and validate different models? also what is the best ways to build a validation set from scratch?