Rough Set Approach to Generate Classification Rules for diabetes
In the current age medical science improved to certain height but some commonly disease like diabetes provide lots of symptoms , it is very tedious task to find the best fit symptom for diabetes to get accurate symptoms for diabetes we develop a technique using rough set concept which is prcised and accurate up to certain extent. To start with, we take 100 samples and then using correlation techniques we consider 20 samples for our purpose, then apply rough set concept to find minimum number of symptoms for diabetes
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ABOUT THE AUTHORS
Sujogya Mishra
Sujogya Mishra Currently working as Research scholar Utkal university Bhubaneswar. Area of interest is Data minig, design Algorith analysis, fractal analysis.
Shakti Prasad Mohanty
Eminent Professor, more than 30 years of teaching Experience Producing several PhD in Mathematics, Area of Interest is coding theory , Probability statistics currently working in the field of data mining
Sateesh Kumar Pradhan
Eminent Professor his area research include ,Parallel Algorithms, History of Reading, Computer Course and currently working in the field Prallel & Distributed Computing, Neural Computing, Mobile Computing
Sujogya Mishra
Sujogya Mishra Currently working as Research scholar Utkal university Bhubaneswar. Area of interest is Data minig, design Algorith analysis, fractal analysis.
Shakti Prasad Mohanty
Eminent Professor, more than 30 years of teaching Experience Producing several PhD in Mathematics, Area of Interest is coding theory , Probability statistics currently working in the field of data mining
Sateesh Kumar Pradhan
Eminent Professor his area research include ,Parallel Algorithms, History of Reading, Computer Course and currently working in the field Prallel & Distributed Computing, Neural Computing, Mobile Computing
