Usage the lazy learning meta-heuristic technique for predicting entrepreneurial marketing in the insurance industry

Due to the increasing importance of marketing, entrepreneurship and the role of organizational structure in their application, the purpose of this research is to predict entrepreneurial marketing using an organizational structure in the insurance industry. For this purpose, for marketing, seven indicators and for organizational structure, three indicators are defined, then prediction of entrepreneurial marketing indicators has been done by organizational structure indicators using lazy learning algorithm. In the proposed method, after predicting each data by K vector from its closest neighbor, the algorithm database is enriched for better prediction of future data. The proposed algorithm is simulated and compared in five different modes by MATLAB software, also, three insurance (Iran, Karafarin and Parsiyan) companies are selected in Mazandaran province. In total, the statistical population in this study is 588 cases. The results of simulation indicate the proper accuracy of entrepreneurial marketing forecasting based on validation parameters MSE and NRMSD. In this research, Lazy Learning method can predict future without modeling the problem with previous information processing.