What do I have wrong here?

# Your code to train knn, make predictions, and compute accuracy goes in here

#accuracy = # compute accuracy here

Employee_attrition is the data.

1. Train a knn model where k is 3 using the training dataset. 2. Make predictions using the test dataset 3. Compute accuracy and save as accuracy - Hints: - You need to use the KNeighborsClassifier function. Instantiate a knn object and pass the number of neighbors to the function. Train the model using the X _train and ytrain. Then make predictions using X _test. Then compute the accuracy using the predicted values and y test. - Check Module 6d: Model Performance and_Module 5c: Classification 4]: from sklearn.neighbors import KNeighborsclassifier from sklearn.metrics import confusion_matrix knn = KNeighborsclassifier(n_neighbors = 3) knn.fit(X_train, y_train) cm = confusion_matrix (y test, knn.predict(X_test) ) accuracy =(cm[,0]+cm[1,1])/sum(sum(cm)) accuracy