From the course: Machine Learning and AI: Advanced Decision Trees with SPSS
Unlock the full course today
Join today to access over 23,200 courses taught by industry experts.
XGBoost Tree node
From the course: Machine Learning and AI: Advanced Decision Trees with SPSS
XGBoost Tree node
- [Instructor] Okay, so we've seen the checkbox boosting option and we've oriented ourselves to a little bit of what to expect from XGBoost. So let's give XGBoost a try right here in Modeler, picking up in the same stream where we lift off. So we want to go to the Python tab, and over here in the Python tab we see XG Boost Stream. Even though this is implemented through Python, it looks just like any other modeling node would. So we'll go ahead and connect it. We're going to keep all the settings the same and let's take a look inside. So we've got everything coming in from the type node. We have all the same variables that I ran using the checkbox style of boosting. But if we go to build options, we're presented with a lot of stuff going on here. We have different methods from model building, and as I warned you to anticipate, we have this learning task option. We also have hyper parameters, like early stopping as you…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Contents
-
-
-
-
-
(Locked)
Ensembles4m 48s
-
(Locked)
What is bagging?7m 19s
-
(Locked)
Using bagging for feature selection3m 55s
-
(Locked)
Random forests2m 57s
-
(Locked)
What is boosting?3m 32s
-
(Locked)
What is XGBoost?1m 55s
-
(Locked)
XGBoost Tree node2m 56s
-
(Locked)
Costs and priors5m 11s
-
(Locked)
XGBoost Linear1m 50s
-
(Locked)
-