Gradient Boosting: Ensemble Methods, Predictive Modeling, and Machine Learning
Gradient boosting is a machine learning technique for regression problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees. It builds the model in a stage-wise fashion like other boosting methods do, and it generalizes them by allowing optimization of an arbitrary differentiable loss function. Gradient boosting method can be also used for classification problems by reducing them to regression with a suitable loss function.
If this is your time using Gradient Boosting, you have come to the right place. This website should get you up and running quickly and easily.
Start off by registering with the site so you can get updates and receive articles on Predictive Modeling news.