The game of Hex is the board game with simple rules and is classified as a two-player, zero-sum, logical perfect information game. The game proceeds by putting their pieces in turn on empty cells of the board. A player wins if the player connects the two opposing sides of the board with their own color pieces. Our previous study clarified that it is effective to develop a computer Hex strategies with the network characteristics as the evaluation function to evaluate the board states from the global and local perspectives and showed that there is the best parameter to decide the ratio between global and local evaluation during a match. In order to go beyond the strategy, we hypothesize that the ratio must change during a match depending on the board states as human players differently evaluate the board states at the beginning, middle and final stages. First, we examine the hypothesis whether the better wining rate can be achieved by changing the ratio of global and local evaluation and propose a novel computer Hex program that can evaluate the board states while changing the global and local evaluation by recognizing the board states with SVM. Our proposed method is evaluated with the current world-champion program called MoHex.