1. MIS 451 Building Business Intelligence Systems Clustering (1)

2. 2 Problem Target Marketing Diaper, Baby food, Swiss cheese and Belgian Toyschocolate French Wine

3. 3 Clustering Clustering is a data mining method for grouping data points such that data points within the same cluster are similar and data points in different clusters are dissimilar. How to calculate similarity between data points??

4. 4 Measuring Similarity Continuous variable Use distance to measure dissimilarity between data points For two data points, distance between them can be measured in two ways Manhattan distance Euclidean distance

5. 5 Measuring Similarity For two continuous data points X, Y, Manhattan distance is defined as:

6. 6 Measuring Similarity Example of Manhattan distance NAMEAGESPENDING($) Sue212300 Carl272600 TOM455400 JACK526000

7. 7 Measuring Similarity For two continuous data points X, Y, Euclidean distance is defined as:

8. 8 Measuring Similarity Example of Euclidean distance NAMEAGESPENDING($) Sue212300 Carl272600 TOM455400 JACK526000 Reading: Data mining book PP335- 341