Classification rules mining based on SOFM networks

摘要

Self-organization feature mapping (SOFM) networks have strong ability for self-learning and self-adaptive. According to the characteristics of human thought, this paper constructed a kind of combined criterion, which may be used to guide the learning of self-organization feature mapping network. Then this paper presents subsection algorithm, amalgamation algorithm and dynamical adaptive algorithm for SOFM networks so as to solve a kind of problems of classification rule mining. Finally, a practical example shows its flexibility and practicability.