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Raphael
Raphael
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Tweeted twitter.com/StackCompSci/status/684930077948272640
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David Richerby
David Richerby
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I don't see why overfitting in machine learning Why is unwanted when it can be de/re-incremented and end up finding the best, strongest actionsoverfitting bad?

I'vI've studied this lots, and they say overfitting the actions in machine learning is bad, yet our neurons do become very strong and find the best actions/senses that we go by or avoid, plus can be de-incremented/incremented from bad/good by bad or good triggers, meaning the actions will level and it ends up with the best(right), super strong confident actions. How does this fail? It uses positive and negative sense triggers to de/re-increment the actions say from 44pos. to 22neg.

I don't see why overfitting in machine learning is unwanted when it can be de/re-incremented and end up finding the best, strongest actions

I'v studied this lots, and they say overfitting the actions in machine learning is bad, yet our neurons do become very strong and find the best actions/senses that we go by or avoid, plus can be de-incremented/incremented from bad/good by bad or good triggers, meaning the actions will level and it ends up with the best(right), super strong confident actions. How does this fail? It uses positive and negative sense triggers to de/re-increment the actions say from 44pos. to 22neg.

Why is overfitting bad?

I've studied this lots, and they say overfitting the actions in machine learning is bad, yet our neurons do become very strong and find the best actions/senses that we go by or avoid, plus can be de-incremented/incremented from bad/good by bad or good triggers, meaning the actions will level and it ends up with the best(right), super strong confident actions. How does this fail? It uses positive and negative sense triggers to de/re-increment the actions say from 44pos. to 22neg.

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Friendly Person 44
Friendly Person 44
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I don't see why overfitting in machine learning is unwanted when it can be de/re-incremented and end up finding the best, strongest actions

I'v studied this lots, and they say overfitting the actions in machine learning is bad, yet our neurons do become very strong and find the best actions/senses that we go by or avoid, plus can be de-incremented/incremented from bad/good by bad or good triggers, meaning the actions will level and it ends up with the best(right), super strong confident actions. How does this fail? It uses positive and negative sense triggers to de/re-increment the actions say from 44pos. to 22neg.