Research on the Design of Parallel Hypernetworks Model Based on Hadoop Cloud Computing Platform

Abstract

The evolutionary hypernetwork is a kind of cognitive learning model inspired by biological networks and the hypernetwork model has been successfully applied in plenty of fields. But the hypernetwork model may lead to a huge amount of hyperedges in the process of high dimensional data, which is the bottleneck of the single machine hardware implementation. In order to solve this problem, this paper presents the parallel model of hypernetwork computation under the Hadoop cloud computing platform, which changes single machine algorithm to multiple machines. Empirical studies on the acute leukemia dataset result demonstrate that the proposed hypernetwork classifier of parallel evolutionary hypernetwork model based on the Hadoop cloud computing platform has higher classification accuracy rate and good scalability. This is the main advantage of the parallel evolutionary hypernetwork model.