Balancing cost and model size.
Thanks for the update. Will help learning new concepts.
Happy to help, Kandasamy :)
That is very interesting. I always hated how Decision Trees showed overfitting when displaying decision zones. Much appreciated.
Same here, KG :)
Thanks for appreciating.
You may want to write a similar text for XGBoost and Random Forests. They all suffer from the same disease
As far as I have seen, random forest are quite robust to this. While the individual decision tree may overfit the bootstrapped data, the whole decision tree is somewhat robust and does not entirely overfit the whole training data.
Thanks for the update. Will help learning new concepts.
Happy to help, Kandasamy :)
That is very interesting. I always hated how Decision Trees showed overfitting when displaying decision zones. Much appreciated.
Same here, KG :)
Thanks for appreciating.
You may want to write a similar text for XGBoost and Random Forests. They all suffer from the same disease
As far as I have seen, random forest are quite robust to this. While the individual decision tree may overfit the bootstrapped data, the whole decision tree is somewhat robust and does not entirely overfit the whole training data.