HW5 - 1. Description of how you measured the cluster...

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Project 3: Clustering Start date Nov 13 The goal of this project is to choose and evaluate clustering mechanisms. I would suggest using the mechanisms available in Weka or RapidMiner, although you may implement your own if you wish. Use Image Segmentation, housing and Isolet datasets from the UCI Machine Learning Repository . What you need to do for this project is: Determine how you will measure the quality of the clusters produced. Choose two algorithms to compare. Set up and run a comparison experiment, obtaining the quality measures you determined above. Explain which algorithm you would use for what types of data and why Project Report The project report should contain the following:
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Unformatted text preview: 1. Description of how you measured the cluster quality (this will include a brief overview of the datasets.) 2. Discussion of each of the four experiments, consisting of: 1. How you prepared the data 2. Parameters chosen for the algorithm 3. Experimental result summary. For each, you should include a brief discussion of why you made the decisions you did. 3. Conclusions: General discussion of the appropriate conditions for use of each algorithm. You may instead want to frame this as a discussion of appropriate type of algorithm for a general category of data (probably a more difficult task, but also more interesting.) You should also include the output from your sample runs....
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This note was uploaded on 08/29/2011 for the course CAP 4770 taught by Professor Staff during the Fall '08 term at FIU.

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HW5 - 1. Description of how you measured the cluster...

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