A dynamic gradient boosting machine using genetic optimizer for practical breast cancer prognosis
作者：
Highlights：
• Devising an adaptive gradient boosting model using online weak learners.
• Enhancing the online boosting performance using a genetic optimizer.
• Dynamic breast cancer prognosis using the proposed technique.
• Comprehensive evaluation on state-of-art online learning techniques.
• Validation of the proposed technique on benchmark datasets.
摘要
•Devising an adaptive gradient boosting model using online weak learners.•Enhancing the online boosting performance using a genetic optimizer.•Dynamic breast cancer prognosis using the proposed technique.•Comprehensive evaluation on state-of-art online learning techniques.•Validation of the proposed technique on benchmark datasets.
论文关键词：Breast cancer prognosis,Online learning,Gradient boosting,Genetic algorithm,Adaptive linear regression
论文评审过程：Received 5 April 2018, Revised 15 July 2018, Accepted 24 August 2018, Available online 28 August 2018, Version of Record 22 September 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.08.040
