- KNN is a Supervised Learning
- AKA lazy learner
- as it doesn't learn anything from the data
- But memorize the whole train data
- and classify a new point
- Steps
- Start with a labeled data
- For a new data
- Find K-nearest neighbors
- Assign to the major voted ones
- Assign K to a odd number to avoid ties
- If still ties, take Random neighbor or disregard the data
- Find optimal K using dev data
- Too Low values of K is noisy and susceptible to outliers
- Too Large values of K can always classify as the most data ones
- Distance Metric: