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Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
Weka project  - DataMining
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Weka project - DataMining

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Weka project - DataMining …

Weka project - DataMining
بإستخدام بيانات تخطيط القلب من إحدى المستشفيات

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  • 1. ‫‪ ‬ا‪ ‬ا‪ ‬ا‪‬‬ ‫ﺟﺎﻣﻌﺔ اﻟﻨﻴﻠﻴﻦ‬ ‫ﻛﻠﻴﺔ ﻋﻠﻮم اﻟﺤﺎﺳﻮب وﺗﻘﺎﻧﺔ اﻟﻤﻌﻠﻮﻣﺎت‬ ‫ﻣﺎﺟﺴﺘﻴﺮ ﺗﻘﺎﻧﺔ اﻟﻤﻌﻠﻮﻣﺎت‬ ‫اﻟﻤﺠﻤﻮﻋﺔ اﻟﺜﺎﻧﻴﺔ‬ ‫ ‪Model By Weka (Echocardiogram Data) Using‬‬ ‫ )‪Classification Model (Desion Tree‬‬ ‫ﺑﻴﺎﻧﺎت ﺗﺨﻄﻴﻂ اﻟﻘﻠﺐ‬ ‫إ‪‬اد ا‪:‬‬ ‫ﺻﻔﻴﻪ ﻧﺎﺟﺢ ﻧﻮري اﻟﺒﺪري‬ ‫إ‪‬اف :‬ ‫دﻛﺘﻮر ﻣﺤﻤﺪ ﻋﺜﻤﺎن ﻋﻠﻲ ﺣﺠﺎزي‬ ‫1‬
  • 2. ‫ﻳﻮﺟﺪ اﻟﻜﺜﻴﺮ ﻣﻦ اﻟﻤﺮﺿﻰ اﻟﺬﻳﻦ ﻋﺎﻧﻮ ﻣﻦ اﻟﻨﻮﺑﺎت اﻟﻘﻠﺒﻴﻪ ﻓﻲ ﻣﺮﺣﻠﺔ ﻣﺎ ﻓﻲ‬ ‫ﺣﻴﺎﺗﻬﻢ ، ﺑﻌﺾ اﻟﻤﺮﺿﻰ ﻻﻳﺰاﻟﻮن ﻋﻠﻰ ﻗﻴﺪ اﻟﺤﻴﺎة وﺑﻌﻀﻬﻢ ﻻ ، ﻓﺒﺄﺧﺬ اﻟﻌﺪﻳﺪ ﻣﻦ‬ ‫اﻟﻤﺘﻐﻴﺮات ﻣﻊ ﺑﻌﻀﻬﺎ اﻟﺒﻌﺾ ﻳﻤﻜﻦ اﻟﺘﻨﺒﺆ إذا ﻛﺎن اﻟﻤﺮﻳﺾ ﺳﻴﺒﻘﻰ ﻋﻠﻰ ﻗﻴﺪ اﻟﺤﻴﺎة‬ ‫ﻟﻤﺪة ﺳﻨﺔ واﺣﺪ ﻋﻠﻰ اﻷﻗﻞ ﺑﻌﺪ اﻟﻨﻮﺑﻪ اﻟﻘﻠﺒﻴﻪ أم ﻻ .‬ ‫اﻟﻤﺸﻜﻠﻪ اﻟﺘﻲ ﺗﻮاﺟﻪ اﻟﺒﺎﺣﺜﻮن ﻫﻲ اﻟﺘﺒﺆ ﻣﻦ اﻟﻤﺘﻐﻴﺮات اﻷﺧﺮى )ﻫﻞ ﺳﻴﺒﻘﻰ‬ ‫ﻋﻠﻰ ﻗﻴﺪ اﻟﺤﻴﺎﻩ ﻣﺪة ﺳﻨﻪ واﺣﺪﻩ ﻋﻠﻰ اﻷﻗﻞ أم ﻻ ؟( ، أﺻﻌﺐ ﺟﺰء ﻣﻦ ﻫﺬﻩ‬ ‫اﻟﻤﺸﻜﻠﻪ ﻫﻮ اﻟﺘﻨﺒﺆ ﺑﺸﻜﻞ ﺻﺤﻴﺢ ﺑﺄن اﻟﻤﺮﻳﺾ ﻟﻦ ﻳﻨﺠﻮ )وﺣﺠﻢ ﻣﺠﻤﻮﻋﺔ‬ ‫اﻟﺒﻴﺎﻧﺎت ﻫﻮ ﺟﺰء ﻣﻦ اﻟﺼﻌﻮﺑﻪ( .‬ ‫ ‪DataSet : Echocardiogram Data‬‬ ‫2‬
  • 3. Number of Attributes: 12 Attribute Information: 1. (survival) : the number of months patient survived (has survived, if patient is still alive). Because all the patients had their heart attacks at different times, it is possible that some patients have survived less than one year but they are still alive. Check the second variable to confirm this. Such patients cannot be used for the prediction task mentioned above. 2. (still-alive) : a binary variable. D=dead at end of survival period, L means still alive . 3. (age at heart attack) : age in years when heart attack occurred. 4. (pericardial effusion) : binary. Pericardial effusion is fluid. around the heart. 0=no luid, 1= luid . 5.( fractional shortening ) : a measure of contracility around the heart lower numbers are increasingly abnormal . 6. (epss) : E-point septal separation, another measure of contractility. Larger numbers are increasingly abnormal. 7. (lvdd) : left ventricular end-diastolic dimension. This is a measure of the size of the heart at end-diastole. Large hearts tend to be sick hearts. 8. (wall motion score) : a measure of how the segments of the left ventricle are moving . 9.( wall motion index) : equals wall-motion-score divided by number of segments seen. Usually 12-13 segments are seen in an echocardiogram. Use this variable INSTEAD of the wall motion score. 10. (mult) : a derivate var which can be ignored . 11. (group) : meaningless, ignore it . 12. (alive at one)(class) : Derived from the first two attributes. (N) means patient was either dead after 1 year or had been followed for less than 1 year. (Y) means patient was alive at 1 year. Distribution of attribute number 2: still-alive Value Number of instances with this value ---- ----------------------------------D 40 (dead) L 21 (alive) Total 61 3
  • 4. Distribution of attribute number 13: alive-at-1 Value Number of instances with this value ---- ----------------------------------N 44 Y 17 Total 61 The Application : 4
  • 5. 5
  • 6. Visualize All: Discretize: 6
  • 7. Apply Discretize: 7
  • 8. Visualize All After Descrize : Classify Using Tree(J48) : 8
  • 9. Select The Class Attribute : 9
  • 10. Classify Output : 10
  • 11. Visualize Tree: 11
  • 12. Tree View : 12
  • 13. Visualize Classifier Errors : 13
  • 14. 14
  • 15. Select Attributes : Visualize : 15
  • 16. 16
  • 17. Knowledge Flow : 17
  • 18. 18
  • 19. Model(1) : Result of Model(1) : 19
  • 20. Model(2) : Result of Model(2) Using Text Viewer : 20
  • 21. Result of Model(2) Using Graph Viewer : Result Of Model : Distribution of attribute number still-alive Value Number of instances with this value No = 24.0 . Yes = 14.0/2.0 . 21

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