Lossy compression is called "lossy" for a reason.
As for overfitting, these are literally the first words from your link:
> Overfitting occurs when a model or algorithm memorizes and fits too closely or exactly to its training data. Overfitting results in a model that might not be able to make accurate predictions or conclusions from any data other than the training data and potentially fails in unexpected scenarios.
Compare that with my post to see which of us knows what we are talking about and who don't.
> Let me guess - in your worldview anyone who does not agree with your definitions is wrong?
First, not "my definition" but the classic definitions that [even your own link from IBM](https://www.ibm.com/docs/en/watsonx/saas?topic=atlas-overfitting ) adopts.
Second it's **you** that [2 days ago replied](https://swecyb.com/users/troed/statuses/117129386789508695 ) to me
> Your claim is factually > **wrong**> and shows that you lack knowledge on the topic you're posting about.
Look at the mirror, but do not despair: ignorance is a natural condition of human beings, a step in a journey, some times starting point, some times destination. The problem is never ignorance but wrong unchallenged beliefs.
Giacomo Tesio
npub1ng…qgmse
2026-08-23 19:00:35 UTC
in reply to nevent1q…gn5g
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2026-08-23 19:00:35 UTCEvent JSON
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"content": "Lossy compression is called \"lossy\" for a reason.\n\nAs for overfitting, these are literally the first words from your link:\n\u003e Overfitting occurs when a model or algorithm memorizes and fits too closely or exactly to its training data. Overfitting results in a model that might not be able to make accurate predictions or conclusions from any data other than the training data and potentially fails in unexpected scenarios.\nCompare that with my post to see which of us knows what we are talking about and who don't.\n\u003e Let me guess - in your worldview anyone who does not agree with your definitions is wrong?\nFirst, not \"my definition\" but the classic definitions that [even your own link from IBM](https://www.ibm.com/docs/en/watsonx/saas?topic=atlas-overfitting ) adopts.\n\nSecond it's **you** that [2 days ago replied](https://swecyb.com/users/troed/statuses/117129386789508695 ) to me\n\u003e Your claim is factually \u003e **wrong**\u003e and shows that you lack knowledge on the topic you're posting about.\nLook at the mirror, but do not despair: ignorance is a natural condition of human beings, a step in a journey, some times starting point, some times destination. The problem is never ignorance but wrong unchallenged beliefs.",
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