CSE 572-DM-Huan.Liu-S10-HW5-Clustering_1

CSE 572-DM-Huan.Liu-S10-HW5-Clustering_1 - School of...

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Data Mining (CSE 572), ASU, Spring 2010, Huan Liu http://www.public.asu.edu/~huanliu/DM10S/cse572.html Page 1 From 2 School of Computing, Informatics, and Decision Systems Engineering Data Mining (CSE 572) Spring 2010 Instructor: Dr. Huan Liu TA: Mohammad Ali Abbasi Homework # 5, Clustering Deadline Monday, April 5 th , 2010 How to submit Hard copy in the Class; before the class HW5-1: Consider the points in the following table. Point X Y P1 2.0 2.5 P2 2.0 5.5 P3 3.0 2.5 P4 3.0 4.5 P5 4.0 3.5 P6 6.0 7.0 a) Perform two iterations of the K-means algorithm in order to obtain two clusters for the input instances given in table 1. Assume that the first centers are the instances 1 and 3. Explain if more iterations are needed in order to get the final clusters. b) What is the usual shape of clusters generated by K-means? Give an example of cases where K-means has limitation in detecting the patterns formed by the data points.
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Data Mining (CSE 572), ASU, Spring 2010, Huan Liu http://www.public.asu.edu/~huanliu/DM10S/cse572.html
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This note was uploaded on 04/08/2010 for the course CS 420 taught by Professor Dawsonengler during the Spring '02 term at San Jose State University .

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CSE 572-DM-Huan.Liu-S10-HW5-Clustering_1 - School of...

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