@lachinemearning.com: bagging? boosting? these are machine learning methodologies that leverage parralelism and sequences when building ensembles #aiml #computerscience #technology #machinelearning #llm

iris
iris
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Wednesday 15 April 2026 07:22:57 GMT
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ohboioh8
ohboi oh :
Thoughts on mythos NOW
2026-04-15 10:49:07
0
whereami269
whereami269 :
I don't understand anything 😭
2026-04-15 16:33:20
0
snnsaint
sin :
very interesting, thank you for the video!
2026-04-26 22:10:23
0
codexo98
codexo :
Is random forest bagging?
2026-04-17 04:50:15
1
minteb57
Madstop :
Xg like expected goals
2026-04-15 08:48:46
2
freddypettit6
🦅 :
Bro why am i blocked on my other account 😢. Anyways is boosting always better than bagging? When would you use bagging (other than when ur especially worried about overfitting)
2026-04-15 17:56:44
1
i_x_9_x_i
fantalight :
based
2026-05-28 22:33:32
0
pterodactylptodd
Todd Denaro :
Can you go over k-fold cross validation? Or would you use k-fold in a random forest model? Also, why 70%:30% train test split instead of 80%:20% or something else?
2026-04-16 07:27:27
0
lagrange248
Алёшенька :
yes dataset correct!
2026-04-15 09:21:45
0
funperefagha0
Funperefagha :
Thank you again 😌
2026-04-15 07:34:51
2
_orlodx
orlo :
A classic
2026-04-15 08:25:32
1
jeff_null
Jeff🐾 :
👍👍
2026-06-11 16:13:58
0
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