摘要
LogitBoost由于其解趋近于贝叶斯最优解,并且实现简单,因而成为机器学习中研究的热点,是直接优化二项对数损失的Ada boost算法。首次将LogitBoost的分类算法应用于网络误用检测中,实验结果表明,LogitBoost检测性能优于目前常用的模式匹配算法。
LogitBoost is one of the Adaboost algorithms that directly optimizes the binomial log-likelihood.Because of its solution approxi mates to Bayesian and it is easy to implement,LogitBoost becomes the hot topic in machine learning.In this paper,the LogitBoost classifi cation technique is first applied in network misuse detection.The result of experiments shows that LogitBoost has better performance than the other common Pattern Match algorithms.
出处
《电脑知识与技术》
2011年第11X期8172-8174,共3页
Computer Knowledge and Technology
