Supervised Learning - Classification Week 8 Challenge

Q1. Apply knn to the “Surface defects in stainless steel plates” and identify the differences

Ans: In .ipynb file

2) What are the pros and cons of knn

Pros :

• No training period required hence also called as lazy learning algorithm
• Easy to implement
• Many new data can be added without any changes to the model

Cons :

• Does not work well with high dimensional data
• Feature scaling is required
• Sensitive to noisy data and outliers