knn_misclassification_rate = np.zeros(3)
for index, k in enumerate([1, 5, 10]):
knn = sklearn.neighbors.KNeighborsClassifier(n_neighbors=k)
knn.fit(X_train, y_train)
knn_result = knn.predict(X_test)
knn_misclassification_rate[index] = np.mean(knn_result != y_test)
plt.figure()
plt.plot(1 / np.array([1, 5, 10]), knn_misclassification_rate, "-bo")
plt.suptitle("Misclassification rate v.s. 1/k of KNN")
plt.show()
print(knn_misclassification_rate)
# Question 5 #
k_nearest_neighbors = KNearestNeighbors(1)
k_nearest_neighbors.fit(X_train, y_train)
knn_result = k_nearest_neighbors.predict(X_test)
knn_naive_misclassification_rate = np.mean(knn_result != y_test)
print(knn_naive_misclassification_rate)
# Question 7 #
w_knn_misclassification_rate = np.zeros(3)
for index, k in enumerate([1, 5, 10]):
knn = WeightedKNearestNeighbors(n_neighbors=k)
knn.fit(X_train, y_train)
knn_result = knn.predict(X_test)
w_knn_misclassification_rate[index] = np.mean(knn_result != y_test)
plt.figure()
plt.plot(1 / np.array([1, 5, 10]), w_knn_misclassification_rate, "-bo")
plt.suptitle("Misclassification rate v.s. 1/k of weighted KNN")
plt.show()
