import numpy as np
from sklearn.neighbors import KNeighborsClassifier

# Assume that we have X_train (input features) and y_train (labels) for training
# and X_test (input features) for testing

# Set the number of neighbors to use
k = 5

# Create the model
knn = KNeighborsClassifier(n_neighbors=k)

# Train the model on the training data
knn.fit(X_train, y_train)

# Make predictions on the test data
predictions = knn.predict(X_test)

# Check the accuracy of the predictions
accuracy = np.mean(predictions == y_test)
print("Accuracy:", accuracy)
