Finding Important Features Using XGBoost

XGBoost is a decision-tree-based ensemble Machine Learning algorithm that uses a gradient boosting framework. In prediction problems involving unstructured data (images, text, etc.) artificial neural networks tend to outperform all other algorithms or frameworks. However, when it comes to small-to-medium structured/tabular data, decision tree based algorithms are considered best-in-class right now.

XGBoost and Gradient Boosting Machines (GBMs) are both ensemble tree methods that apply the principle of boosting weak learners (CARTs generally) using the gradient descent architecture. However, XGBoost improves upon the base GBM framework through systems optimization and algorithmic enhancements.

For more details, please find the link below:

If you enjoyed it, please follow me on Medium for more. It’s great cardio for your 👏 AND will help other people see the story.

If you want to continue getting this type of article, you can support me by becoming a Medium subscriber. It costs $5/month. A part of your subscription fee goes to me.

Related posts:

Olho-te com meus olhos curiosos Procurando e percorrendo seus detalhes Os mínimos e escondidos detalhes Nas tuas curvas e traços sinuosos A volúpia de mim toma conta Quando tu me encosta E teus…

Originally developed to ensure the legitimacy of digital currency transactions (by tracking them in a public distributed ledger), Blockchain is now serving endless protective as well as disruptive…

This makes sense. There isn’t much else to do, so we turn to our devices. Meaning that screen time has increased for many of us, as well as social media usage. Not only are we relying on it for…