Reference no: EM133047807

1. How is a data mining different from a database?

2. Present an example where data mining is crucial to the success of a business.

3. Explain the difference and similarity between discrimination and classification, between characterization and clustering, and between classification and regression

4. Describe three challenges to data mining a regarding data mining methodology and user interaction issue.

5. Outline the major research challenge of data mining in one specific application domain, such as stream/sensor data analysis, spatiotemporal data analysis, or bioinformatics.

6. Briefly outline how to compute the dissimilarity between objects described by the following: (a) Nominal attributes (b) Binary attributes (c) Numeric attributes.

7. Briefly outline how to compute the visualization techniques described by the following: (a) Pixel-oriented (b) Geometric-based (c) Parallel coordinates

8. Define what is the data preprocessing and explain four steps.

9. In real-world data, tuples with missing values for some attributes are a common occurrence. Describe various methods for handling this problem.

10. Briefly outline the normalization methods and show an example

Attachment:- Assignment-Data Mining.rar