| 000 | 01516nam a2200253 a 4500 | ||
|---|---|---|---|
| 001 | vtls000067835 | ||
| 003 | KUKTEM | ||
| 005 | 20251114204532.0 | ||
| 008 | 121219t2012 my da f m 000 0 eng d | ||
| 020 | _aTHE0002011(Local) | ||
| 039 | 9 |
_a201905131603 _byusri _c201401220917 _dFida _c201401220917 _dFida _y201212191030 _zFida |
|
| 040 | _aUMP | ||
| 090 | _aQA278 .A45 2012 rs Bc. | ||
| 100 | 0 | _aMohd Amirol Redzuan Mat Rofi | |
| 245 | 1 | 0 |
_aData clustering using max-max roughness and its application to cluster patients suspected heart disease / _cMohd Amirol Redzuan Mat Rofi |
| 260 |
_aKuantan, Pahang : _bUMP, _c2012 |
||
| 300 |
_axiii, 128 p. : _bill. (some col.) ; _c30 cm. + _e1 CD-ROM |
||
| 502 | _aProject paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2012 | ||
| 504 | _aBibliography: p. 126-128 | ||
| 520 | 3 | _aNowadays, there are many technique to clustering large-scale data. One of the technique to clustering data is using the Rough Set Theory.The objective of this paper is to present the process of Data Clustering Using Maximum-Maximum Roughness and its application to cluster patients suspected heart disease. It is based on clustering techniques based on rough set theory name Max-Max Roughness to describes and employed regarding to solve a classification problem of heart disease patients. | |
| 650 | 0 | _aCluster analysis | |
| 650 | 0 | _aData mining | |
| 999 |
_aVIRTUA40 _c3716 _d3722 |
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| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992 | ||