hompi.sogang.ac.krhompi.sogang.ac.kr/jinhwakim/csm/cluster_e-miner.docx · web viewjung 55 55 12...

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Cluster Analysis using E-miner 1. In Excel, type below data Name age incom e educatio n LEE 30 50 12 KIM 34 60 16 PARK 47 70 18 JUNG 55 55 12 CHOI 35 58 16 CHOI 42 70 18 MIN 47 45 12 KANG 29 36 12 SEO 50 56 12 2. Save the file as ‘test-cluster’. 3. Open SAS 4. Choose ‘data import’ as below 1

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Page 1: hompi.sogang.ac.krhompi.sogang.ac.kr/jinhwakim/csm/Cluster_E-miner.docx · Web viewJUNG 55 55 12 CHOI 35 58 16 CHOI 42 70 18 MIN 47 45 12 KANG 29 36 12 SEO 50 56 12 Save the file

Cluster Analysis using E-miner

1. In Excel, type below data

Name age incom

eeducation

LEE 30 50 12KIM 34 60 16PARK 47 70 18JUNG 55 55 12CHOI 35 58 16CHOI 42 70 18MIN 47 45 12KANG 29 36 12SEO 50 56 12

2. Save the file as ‘test-cluster’.3. Open SAS

4. Choose ‘data import’ as below

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5. Choose ‘Next’ from below.

6. Choose ‘Browse’.

7. Choose ‘background screen’.

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8. choose ‘test-cluster’ from the menu.

9. Click ‘Open’ it.10. Click ‘Next’ from below screen.

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11. Type ‘customer1’ inn below screen.

12. Type ‘customer1’ again in below screen

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13. Close sub small screens below by clicking [x] icon on top right.

14. Choose ‘Solution’, Anlysis’, and ‘Enterprise Miner’ sequentially.

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15. You will have this screen below.

16. From above right click on .

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17. Choose ‘New Diagram’.

18. You then have white screen like this.

19. Push and drag below ‘input data source’ to the screen on the right hand side.

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20. You then have a screen below.

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21. Double click on ‘input data source’. .22. You then will have screen below.

23. Choose select, .9

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24.25. Click button on Library.26. Choose ‘WORK’ from below drop down list.

27. Choose ‘customer1’ and click ‘OK’.

28. You then have the screen below.

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29. Double Click ‘Variable’ from above screen.30. You then have a screen below.

31. Close top right ‘Close’ Button. 32. Save it by click ‘Yes’ in below screnn.

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33. Among menu below, choose ‘Cluster’

34. Push and drag it to the screen as below.

35. Move your cursor to the right had side of ‘WORK.CUSTOMER1’ icon and drag the cursor to the left hand side of icon’Clustering’. You then have screen as below.

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36. Right click on and choose ‘Run’.

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37. You have the screen above as output.

38. Click ‘distance’ .39. The clustered data is as below.

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