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Feb 11, 2023 at 16:52 comment added Dave @Connor If you have some thoughts on the question of mine I linked, I absolutely welcome a post over there.
Jan 11, 2023 at 22:41 comment added Connor Specifically, the part where they say that in higher dimensions all the points tend to spread out so much that there's little difference between their neighbour distances. This would give me exactly the results I'm getting. If the neighbour distances converge to some average, then you would expect the model to reproduce that average and score 0.
Jan 11, 2023 at 22:17 comment added Dave @Connor What do you see as the connection to your question? // I do see some connections, but I appear to be in the minority.
Jan 11, 2023 at 22:15 comment added Connor What do you think of the answer to this question: stats.stackexchange.com/questions/99171/…, seems like this might have some bearing on the issue at hand here!
Jan 11, 2023 at 0:29 comment added Dave @Connor That’s exactly what this formula means! // A score of $R^2=0$ is pretty bad, yes, but $R^2$ can go negative, depending on what you’re doing, and that’s even worse!
Jan 11, 2023 at 0:29 vote accept Connor
Jan 11, 2023 at 0:28 comment added Connor Ahhhh, I get it. So the score is basically saying how well you did vs how well you would do if you guessed the target's mean for everything? In which case, a score of 0 is pretty bad 😅 Thank you! Massive help.
Jan 10, 2023 at 22:21 history edited Dave CC BY-SA 4.0
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Jan 10, 2023 at 22:13 history answered Dave CC BY-SA 4.0