Playing Billiards in Version Space
Playing Billiards in Version Space
复制标题
在版本空间中打台球
作者：
P. Rujan
启发遍历台球的射线跟踪方法被用来估计理论上最好的决策规则为一组给定的线性可分的例子。对于随机分布的例子，具有最佳平均泛化概率的单个感知器的台球估计与已知的分析结果一致，而对于现实生活中的分类问题，与最大稳定性感知器相比，泛化概率不断增强。
A ray-tracing method inspired by ergodic billiards is used to estimate the theoretically best decision rule for a given set of linear separable examples. For randomly distributed examples, the billiard estimate of the single Perceptron with best average generalization probability agrees with known analytic results, while for real-life classification problems, the generalization probability is consistently enhanced when compared to the maximal stability Perceptron.