**Techniques of Decision Support Systems**

Predictive Modeling

1. Discuss any 2 applications of neural network in data mining. Explain how the system could be used (purpose of the system).
2. Discuss and differentiate different type of neural networks.
3. Differentiate single layer from multi-layer neural network
4. Explain/Differentiate the following types of networks:

• Feedforward networks
• Feedback networks
• Lateral networks

5. Differentiate supervised learning, unsupervised learning and reinforced learning.
6. Explain the process to develop an ANN.
7. Explain the concepts of Support vector machine
8. What is a hyperplane
9. What is a kernel function?
10. Explain the purpose of maximizing the margin of the hyperplane.
11. Suggest one solution to resolve a non-linear data boundary.
12. Explain the process of developing an SVM model.
13. Explain the concept of k-nearest neighbor
14. What happen if the k value is too small? Explain.
15. What happen if the k value is too large? Explain.
16. Explain the process of developing a kNN model.