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.
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 coordinate
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1. How is a data mining different from a database2. Present
1. 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.
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 coordinate
