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035 _a.b12354491
099 9 _aAIT RSPR no.ICT-17-03
100 1 _aSindhuja, Sankeneni
245 1 0 _aApplication of data mining techniques to measure cancer morbidity and mortality data
260 _aPathum Thani, Thailand :
_bAsian Institute of Technology,
_c2017
300 _a49 leaves :
_bill.
490 1 _aResearch studies project report ;
_vno. ICT-17-03
500 _aA research submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Information and Communication Technologies, School of Engineering and Technology
502 _aResearch Studies Project Report (M. Eng.) - Asian Institute of Technology, 2017
520 _aIn this modern era cancer is one of the most common disease we are facing everywhere. The cancer rate is increasing enormously the data is huge to classify it we are using data mining techniques. In this report the data is collected from a cancer hospital, Hyderabad. The data is a combination of different cancers age and treatment and mortality. To estimate the statistics of cancer with respect to age, treatment and mortality we are using decision tree classification for classification of data.For performing decision tree we use rapid miner software to analyze the above statistics
650 0 _aData mining
_xTechnological innovations
650 0 _aCancer
_xMortality
700 1 _aGuha, Sumanta,
_eChairperson
700 1 _aPhan, Minh Dung,
_eExamination Committee
700 0 _aAttaphongse Taparugssanagorn,
_eExamination Committee
710 2 _aAIT Fellowship,
_eScholarship donor
810 2 _aAsian Institute of Technology.
_tResearch studies project report ;
_vno. ICT-17-03
856 _3Full-Text
_uhttp://203.159.5.9/ait-thesis/detail.php?q=B08743
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