Binary tree genetic algorithm with quadtree for land cover classifications
Sai-cheong Ng, Kwon-sak Leung · 2004
Enhanced binary tree genetic algorithm (BTGA+) has been successfully applied to land cover classification problems. However, the execution time of BTGA+ is quite long on large datasets. A novel decision tree algorithm, called binary tree genetic algorithm with Quadtree (BTGA with quadtree), is proposed by extending BTGA+. In the proposed algorithm, a generalized Quadtree is constructed when a new node of a linear decision tree is created. The proposed algorithm runs faster than BTGA+ on datasets with sufficiently large number of samples, without sacrificing the quality of decision trees constructed by BTGA+.