Advantages of KNN Algorithm:
- It is simple to implement.
- It is robust to the noisy training data
- It can be more effective if the training data is large.
Disadvantages of KNN Algorithm:
- Always needs to determine the value of K which may be complex some time.
- The computation cost is high because of calculating the distance between the data points for all the training samples.