Thread:Talk:ScalarBot/Version History/how to build a good test bed?/reply (16)

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Latest revision as of 21:56, 3 October 2017

From memory, population size was about 20. It was something between a gradient descent and a genetic algorithm, by moving from the stronger members away from the weaker members, plus some random component. Remember, I had already extracted all of the features etc, and saved them just before inserting into the Kd-Tree, so the only thing I needed at evaluation time was:

  1. read data from file
  2. add points to the tree
  3. KNN/KDE
  4. count inliers vs outliers -> give a score

Then at the end multiply the evolved weights with the code weights, recompile, and collect a new set of data; repeat until happy.

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