1. Explain the difference between clustering and classification.
2. Describe the k-means algorithm.
3. Suppose that you are employed as a data-mining consultant for an Internet search engine company. Describe how data mining can help the company by giving specific examples of how techniques, such as clustering, classification, association rule mining, and anomaly detection can be applied.
4. Explain the reason behind describing artificial neural networks (ANN) as "black box". Then propose one technique to overcome this criticism.
5. Discuss one advantage and one disadvantage of Support Vector Machines (SVM) compared to artificial neural networks (ANN).