1
$\begingroup$

I have a matching algorithm that is based on making an comparison score. This score is divided into parts. Example:

5 - Points for attributes (lets say they have 3 common attributes, would the score be ((3/5)*5) = 3 Points

5 - Points for location

10 - Points for content

Theses points are just something i have set though guessing, and they work well. But to find what values would be best would i like to implement a kind of AI to test this, i have created 20+ test cases where i know what the correct matching is, so i though that i will be able to train my algorithm to have better values for the different value. I am no expert in AI, i have only have one course about it, but would a neural network be able to help me here, or should i go with another AI?

$\endgroup$
1
$\begingroup$

I would suggest you use linear regression, or simply grid search (you can search over all possible number of points for each category, from 1..20; that's only $2^{13}$ possibilities, all of which can be easily tested one-by-one).

Make sure to use cross-validation: split the data set into training and test, and use the training data to derive the best parameters, then evaluate it on the test part.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.