Data mining and computational statistics techniques learned


Investigate data mining/computational/statistical simulation problems and applications that interests them.

The projects should apply data mining and computational statistics techniques learned during the course to real-world problems. Techniques other than those within the course syllabus can also be used, but we strongly recommend having a short discussion with the instructors before deciding to use the chosen technique/methodology.

Data for these projects can be obtained from various internet sites, developed by students or delivered by the instructors (and listed in a separate document).

R is a compulsory tool to be used within the projects. In what follow you will find a tentative list of possible topics which will be updated continuously in the next days.

FINANCE

• Bank customer credit scoring and profiling
• Stock market classification and forecasting
• Principal component regression of time series with many predictors
• Random variable generation for forecasting
• Credit card fraud detection

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Advanced Statistics: Data mining and computational statistics techniques learned
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