You may find that some algorithms cannot be meaningfully applied to some datasets. If this is the case, you need only to explain why in lieu of doing the experiment. However, this case is only acceptable if there is no reasonable way to preprocess the data to make the algorithm apply. Each dataset and algorithm you choose must be used at least once. Explain what you’re looking for, the ideas you learned when exploring the clustering, and what it can tell you about data. Focus on describing what you have discovered.

Please give me quote Master in Computer Science: CS688 Data Mining - Assignment Project Requirements Application-oriented project (due on 31, worth 25% of your course grade, you must score 85/100 in this project to pass): Students will select a dataset, define an application problem, apply three algorithms to solve the problem, and conduct an empirical comparison of the algorithms on the dataset. Outline of the application-oriented project To complete this project, you will need to download and install the Weka Data MiningNote: These repositories contain many data sets, not all of which are appropriate for the mining tasks required here (association rules, classification, clustering), so you will need to do some thinking. With approval, you are also welcome to identify data from other sources, especially those that are of personal interest. Important: You project submissions must also show and include the steps in your work as well as the data/files/source you used; so that your results can be recreated and verified - otherwise you will receive no mark for this project.