CS3708: Decision Support Systems
Semester 1/2010
Course Project: 30%
- Create or choose a suitable dataset for classification. The UCI Machine Learning Archive is a good source of dataset.
- Choose a suitable tool and learn about the tool thoroughly: WEKA, DTREG, XLMiner etc. are to name a few. Go though the documentation (at least the tutorials and examples). (See WEKA tutorial on S-Class)
- Each tool helps you how to preprocess the dataset (such as, discretization, missing value), as well as visualize the dataset. Also help you to build, evaluate and compare each classifier performance (accuracy, error, etc.)
- On 24 September, each student will be asked to make a Presentation. You should introduce your dataset and the kind of preprocessing and analysis you made. Students are expected to use decision tree or regression tree algorithms to analyze the dataset in a comprehensive way and make comparison and conclusions. (10 minutes presentation + 5 minutes Q&A), 15%
- You should also prepare a Report and submit it to me in hardcopy by 1 October. (A sample report is made available on S-Class system for your reference), 15%
- Please feel free to discuss with me about project related query – Talk to me or e-mail me your queries.
- Also note that the Final Exam is scheduled on 1 October, Friday (open book)
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