plt.show() def show_solution(P, T, path): best = load_network(path) Y = best.sim(P) area = plotroc(Y, T) print("") print("Stats for cut = 0.5") [num_correct_first, num_correct_second, total_performance, num_first, num_second, missed] = stat(Y, T) plt.title(path + "\nArea = " + str(area)) plt.show() if __name__ == '__main__': logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger('classify') #P, T = parse_file("/home/gibson/jonask/Dropbox/Ann-Survival-Phd/Two_thirds_of_SA_1889_dataset.txt", targetcols = [5], ignorecols = [0,1,4]) #P, T = parse_file("/home/gibson/jonask/Dropbox/Ann-Survival-Phd/Two_thirds_of_SA_1889_dataset.txt", targetcols = [5], ignorecols = [0,1,3,4]) P, T = loadsyn3(100) find_solution(P, T) #show_solution(P, T, "/export/home/jonask/Projects/aNeuralN/ANNs/Normalized breast/classification_gdblock20_79.6664019063.ann") #show_solution(P, T, "/export/home/jonask/Projects/aNeuralN/ANNs/Normalized breast/classification_gdblock20_78.9515488483.ann") #show_solution(P, T, "/export/home/jonask/Projects/aNeuralN/ANNs/Normalized breast/classification_genetic_80.2223987292.ann") #show_solution(P, T, "/export/home/jonask/Projects/aNeuralN/ANNs/Unnormalized breast/classification_genetic_80.4606830818.ann") #show_solution(P, T, "/export/home/jonask/Projects/aNeuralN/ANNs/Unnormalized breast/classification_gdblock20_79.1104050834.ann")