Hi. In this video we will learn more about the live G B M algorithm.
Live. G B M is, uh,
another very effective algorithm used for many modeling problems, uh,
which is widely adopted, although a little bit less than IG Boost.
It's an supervised learning algorithm used for classification
regression and ranking problems, same as IG Boost. Uh,
with XG Boost, they share a few characteristics. Uh, they are both, uh,
gradient boosting and methods. They support missing values,
uh, GPUs, and also parallelism.
In case of supply. G B M,
it directly supports categorical variables in contrary to XG Boost
where you have to encode them first. Also internally,
AI G B M works a little bit different. Uh,
it uses a different three growth method, uh, than XG Boost.
And also because of this, uh, live G B M is, uh,
a little bit more prone to over fitting.
In our next video, we will make a,
a live G B M model where we will solve a multi classification problem.