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)")
