Early Stopping for Kernel Boosting Algorithms: A General Analysis With Localized Complexities
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2019.2927563
Abstract: Early stopping of iterative algorithms is a widely used form of regularization in statistics, commonly used in conjunction with boosting and related gradient-type algorithms. Although consistency results have been established in some settings, such estimators… read more here.
Keywords: kernel boosting; early stopping; algorithms general; stopping kernel ... See more keywords
Building student’s performance decision tree classifier using boosting algorithm
Sign Up to like & getrecommendations! Published in 2019 at "Indonesian Journal of Electrical Engineering and Computer Science"
DOI: 10.11591/ijeecs.v14.i3.pp1298-1304
Abstract: Student’s performance is the most important value of the educational institutes for their competitiveness. In order to improve the value, they need to predict student’s performance, so they can give special treatment to the student… read more here.
Keywords: performance; adaboost; student performance; scenario ... See more keywords
An overview of cardiovascular disease infection: A comparative analysis of boosting algorithms and some single based classifiers
Sign Up to like & getrecommendations! Published in 2020 at "Statistical journal of the IAOS"
DOI: 10.3233/sji-190609
Abstract: Machine learning is a branch of artificial intelligence that helps machines learn from observational data without being explicitly programmed and its methods have been found to be very useful in the modern age for medical… read more here.
Keywords: boosting algorithms; disease infection; single based; cardiovascular disease ... See more keywords