Hierarchical clustering

Assignment attached.Note: Submit the screenshots of the models (the output results) and answer the questions.

10 points
1.    Produce a hierarchical clustering (COBWEB) model for iris data. How many clusters did it produce? Why? Does it make sense? What did you expect?
Change the acuity and cutoff parameters in order to produce a model similar to the one obtained in the book. Use the classes to cluster evaluation what does that tell you?

10 points
2.    Use the EM clustering method on either the basketball or the cloud data set. How many clusters did the algorithm decide to make? If you change from Use Training set to Percentage evaluation split 66% train and 33% test – how does the evaluation change?

10 points
3.    Use a k-means clustering technique to analyze the iris data set. What did you set the k value to be? Try several different values. What was the random seed value? Experiment with different random seed values. How did changing of these values influence the produced model?

20 points
4.    Choose one of the following three files: soybean.arff,, zoo.arff or zoo2_x.arff and use any two schemas of your choice to build and compare the models. Which one of the models would you keep? Why?

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