Gradient Boosting Machine

Published

Oct 1, 2001

Gradient Boosting Machine is an AI model developed by Stanford University (United States), first published in October 2001. It works in the mathematics domain, on tasks such as pattern classification, binary classification and regression.

Epoch AI has no training-compute estimate for this model. It was trained on roughly 5K datapoints.

The reference paper has 17,891 citations.

Full record

Organization: Stanford University
Country of organization: United States
Domain: Mathematics
Task: Pattern classification, Binary classification, Regression
Dataset size: 5K
Citations: 17,891