Principles of Knowledge Discovery in Data
Projects
Due Date: Variable. See schedule
Percentage overall grade: 39%
Maximum Marks: 100
List of projects:
| Project | Student |
|---|
| Spatial Outlier Detection with Constraints |
Jeff B. & John M. |
| Emmerging Sequences |
Pouria P. |
| Plant Protein Localization |
Vahid |
| Contrast Sets based on Association Rules |
Amit |
| Detecting Harmonic Distortion |
Ken |
| Mammography Classification |
Varun |
| Constraint-Based Frequent Itemset Mining |
Ananth |
| Frequent itemset Mining Algorithm Selection |
Scott |
| Feature Space Conversion for SVM |
Abhishek |
Project demonstrations on Monday and Tuesday April 16-17.
The list of proposed Projects is here.
Due Dates:
| Activity | Due Date |
|---|
| Project Proposal | February 2nd |
| Preliminary "Private" Demo | Week of March 19th |
| Final report submission | April 13thy |
| "Public" Demo | April 16th |
NB: A second "private" preliminary demo can be scheduled later.
Deliverables:
- Project proposal
- 2 pages containing
- Description of the topic of the project
- Methodology intended to address and solve the
issues of the project
- Proposed milestones
- references
- Reasonably documentented source code.
- Executable of the project
- Report explaining the project
- "public" demonstration of the project.
Marking:
Marking will consider the quality of the proposal, the quality of the
report, the quality of the demonstration and to some extent the
quality of the preliminary demo.
Posted on January 24. Updated January 26
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