Data mining with Predictive analysis for healthcare sector: An Improved weighted associative classification approach
Keywords:
classifier, Association rules, data mining, healthcare, Associative Classifiers, CBA, CMAR, CPAR, MCAR
Abstract
Association mining has seen its growth right through data mining during the last few years as it has the ability to search for that entire database that could be of least constraints associated with it.Thus finding such small database sets could be done with the help of predictive analysis method. The paper enlightens the combinational classification of association and classification data mining. For this to happen a new set of constraints need to be introduced namely classification association rule( CAR).some systems like classification systems with domain experts are the ones that can be associated with. For fields like medicine where a lot many patients consult each doctor, but every patient has got different personal details not necessarily may suffer with same disease. So the doctor may look for a classifier, which could provide all details about every patient and henceforth necessary medications can be provided. However there have been many other classification methods like CMAR, CPAR MCAR and MMA and CBA.Some advance associative classifiers have also seen growth very recently with small amendments in terms of support and confidence, thereby accuracy. In this paper we proposed a HIT algorithm based automated weight calculation approach for weighted associative classifier.
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Published
2011-08-15
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Copyright (c) 2011 Authors and Global Journals Private Limited
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