Hyperparameters in XGBoost
Exploring the concept of weak trees, Matt emphasizes their role in building effective gradient boosted decision trees. By starting with simple models and iteratively correcting errors, these models achieve impressive performance. The conversation also highlights the popularity of previous episodes and the impact of video formats on listener engagement.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
681: XGBoost: The Ultimate Classifier — with Matt Harrison
Related Questions
I have a question about the episode 681: XGBoost: The Ultimate Classifier — with Matt Harrison and the clip Decision Trees Explained. How can I make better decisions, and are there any decision trees mentioned?
I have a question about the episode 681: XGBoost: The Ultimate Classifier — with Matt Harrison and the clip Decision Trees Explained. How can I make better decisions and are there any decision trees discussed in those resources?