Discussion Post: Data Mining
Find a dataset suitable for association rule mining and use Orange, Weka, or IPython Notebook to find interesting association rules. You can also use the Java-based SPMF tool.
With SPMF, you can try doing more advanced analysis, such as using multiple-supports and sequential pattern mining.
Make sure the data you find is in a suitable format. Generate the association rules and rank them by the various metrics such as support, confidence, lift, and others. Try to identify the most interesting, useful, and surprising rules based on the combinations of the metrics.
Describe the data, methodology, and results in a formal technical report. Make sure to analyze the results and describe the implications of the rules you have found. Discuss whether they follow from intuition and could they generalize to unseen data.
The response must include a reference list. Using Times New Roman 12 pnt font, double-space, one-inch margins, and APA style of writing and citations.