Research on K-classification covering for PONN
优先排序神经网络K网覆盖分类研究

From the aspect of coverage in the High-Dimensional Space (HDS), we discussed algorithms of Priority Ordered Neural Network (PONN), and promoted K-Partitioning Algorithm (KPA) based on anisotropy in HDS. Benchmark testing and application were made on KPA as well as the comparison with Center Adaptive Selection Algorithm (CASA).The results of experiment prove that the constructive method of KPA is superior to CASA especially in continuous samples.