knn_acc_1_99.py

# Obtain accuracy score varying k from 1 to 99

accuracies = []

for k in range(1,100):
    y_hat_test = knn_predict(X_train, X_test, y_train, y_test, k, p=1)
    accuracies.append(accuracy_score(y_test, y_hat_test))

# Plot the results 

fig, ax = plt.subplots(figsize=(8,6))
ax.plot(range(1,100), accuracies)
ax.set_xlabel('# of Nearest Neighbors (k)')
ax.set_ylabel('Accuracy (%)');