Humoral-mediated clustering

摘要

This paper describes a novel clustering algorithm inspired by the humoral-mediated response triggered by the adaptive immune system. The key humoral-mediated features of the algorithm include B-cell antibodies produced through plasma cells and memory B-cell antibodies. Affinity threshold, network threshold, death threshold and negative clonal selection threshold are also used to derive intra-cluster and inter-cluster distance metrics that result in the merging of similar clusters and removal/identification of less significant clusters (outlier detection). The performance of the clustering algorithm is tested on both synthetic and real world datasets and compared with other clustering methods.