for run in range(len(naive_data)): naive_x.append(opp) naive_y.append(naive_data[run][opp]) for x, y in human_data: human_x.append(x) human_y.append(y) cobweb_x = np.array(cobweb_x) cobweb_y = np.array(cobweb_y) naive_x = np.array(naive_x) naive_y = np.array(naive_y) human_x = np.array(human_x) human_y = np.array(human_y) cobweb_y_smooth, cobweb_lower_smooth, cobweb_upper_smooth = lowess(cobweb_x, cobweb_y) naive_y_smooth, naive_lower_smooth, naive_upper_smooth = lowess(naive_x, naive_y) human_y_smooth, human_lower_smooth, human_upper_smooth = lowess(human_x, human_y) plt.fill_between(cobweb_x, cobweb_lower_smooth, cobweb_upper_smooth, alpha=0.5, facecolor="green") plt.fill_between(naive_x, naive_lower_smooth, naive_upper_smooth, alpha=0.5, facecolor="red") plt.fill_between(human_x, human_lower_smooth, human_upper_smooth, alpha=0.3, facecolor="blue") plt.plot(cobweb_x, cobweb_y_smooth, label="TRESTLE", color="green") plt.plot(naive_x, naive_y_smooth, label="Naive Predictor", color="red") plt.plot(human_x, human_y_smooth, label="Human Predictions", color="blue")
cobweb_x, cobweb_y = [], [] naive_x, naive_y = [], [] for x,y in cobweb_data: cobweb_x.append(x) cobweb_y.append(y) for x,y in naive_data: naive_x.append(x) naive_y.append(y) cobweb_x = np.array(cobweb_x) cobweb_y = np.array(cobweb_y) naive_x = np.array(naive_x) naive_y = np.array(naive_y) cobweb_y_smooth, cobweb_lower_smooth, cobweb_upper_smooth = lowess(cobweb_x, cobweb_y) naive_y_smooth, naive_lower_smooth, naive_upper_smooth = lowess(naive_x, naive_y) plt.fill_between(cobweb_x, cobweb_lower_smooth, cobweb_upper_smooth, alpha=0.5, facecolor="green") plt.fill_between(naive_x, naive_lower_smooth, naive_upper_smooth, alpha=0.5, facecolor="red") plt.plot(cobweb_x, cobweb_y_smooth, label="COBWEB", color="green") plt.plot(naive_x, naive_y_smooth, label="Naive Predictor", color="red") plt.gca().set_ylim([0.0,1.0]) plt.gca().set_xlim([0,max(naive_x)-1]) plt.title("Incremental Mushroom Edibility Prediction Accuracy") plt.xlabel("# of Training Examples") plt.ylabel("Avg. Probability of True Class (Accuracy)")