Awesome enty

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I tried a few (pretty simple) variants:

  • Multiplying the features by a weight matrix. One nice feature of this is that a diagonal matrix recovers standard feature weighting, so this model should be strictly better than per-feature weights.
  • A one-hidden-layer feedforward network.
  • Summing up the embeddings from the above two.

I totally agree that allowing multiplicative feature interactions as you suggest should work better though!

--Kev (talk)‎19:38, 22 June 2021

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Return to Thread:Talk:BeepBoop/Awesome enty/reply (21).

I'm using no special encoding, just normalizing the features so they are between 0 and 1. Decision-tree-like algorithms have been tried in robocode before (e.g. Wiki_Targeting/Dynamic_Segmentation), but not in conjunction with clustering/KNN as far as I know.

--Kev (talk)‎17:55, 23 June 2021
 
 
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