一种主动式的半监督最近邻学习方法

同时使用标号点和成对约束信息,设计了半监督的最近邻分类算法。为了解决可能无法为某些数据点分配类标号的问题,提出了ratio排序方法以降低冲突点的个数,并采用基于Citation-kNN评分的主动式学习策略,通过获取一些与周围数据点不一致的点的标号来改善半监督学习的效果,以寻找有价值的监督信息。实验结果表明,本文的学习策略可以提高算法的聚类效果,其CRI指标好于COP-kmeans和CCL算法。

Active semi-supervised nearest neighbour learning

A semi-supervised nearest neighbour classification algorithm was proposed,in which both labeled points and pair-wise constraints were employed to determinate the label of data points.To solve the problem that some data points may not be assigned to any class label,the ratio sorting was designed to reduce the number of conflict points.An active learning strategy based on Citation-kNN score was developed to search valuable supervision information and improve the quality of clustering by querying the label of ...