期刊
FRONTIERS IN NEUROROBOTICS
卷 7, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fnbot.2013.00021
关键词
boosting; gradient boosting; machine learning; regression; classification; robotic control; text classification
Gradient boosting machines are a family of powerful machine-learning techniques that have shown considerable success in a wide range of practical applications. They are highly customizable to the particular needs of the application, like being learned with respect to different loss functions. This article gives a tutorial introduction into the methodology of gradient boosting methods with a strong focus on machine learning aspects of modeling. A theoretical information is complemented with descriptive examples and illustrations which cover all the stages of the gradient boosting model design. Considerations on handling the model complexity are discussed. Three practical examples of gradient boosting applications are presented and comprehensively analyzed.
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