A very good repository of data that has been used to test the performance of many data mining algorithms is available at ics.uci.edu/~mlearn/MLRepository.html.

Some of the data sets are meant to test the limits of current machine-learning algorithms and to compare their performance with new approaches to learning.

However, some of the smaller data sets can be useful for exploring the functionality of any data mining software, such as RapidMiner or KNIME. Download at least one data set from this repository (e.g., Credit Screening Databases, Housing Database) and apply decision tree or clustering methods, as appropriate.

Prepare a report based on your results. (Some of these exercises, especially the ones that involve large/challenging data/problem may be used as semester-long term projects.)