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Analysis and Study of the Scope of Improvements in Fitness Advisor Systems using Data Mining


Christy Samuel Raju , Atharva College of Engineering, Malad (W), India; Sanchit V Chavan, Atharva College of Engineering, Malad (W), India; Karan Pithadia, Atharva College of Engineering, Malad (W), India; Shraddha Sankhe, Atharva College of Engineering, Malad (W), India; Prof. Sachin Gavhane, Atharva College of Engineering, Malad (W), India


Fitness, Advice, Clustering, Association, Classification, Data Mining, Health


Today a fair number of health problems can be associated to a person's weight. Tackling this crisis with efficient diagnosis and spreading awareness about body weight related health problems is the need of the hour. The proposed system has a simple principle: "Better solution can be obtained only through better diagnostic methods". The proposed system is an application that advises the user to follow certain procedure to tackle his/her weight related problem. The system identifies three basic user requirements: gaining weight, losing weight and maintaining weight. The system uses data mining to efficiently direct all its users to the best possible solution. Clustering, Classification and Association algorithms are all used in the proposed system.

Other Details

Paper ID: NCTAAP104
Published in: Conference 4 : NCTAA 2016
Publication Date: 29/01/2016
Page(s): 443-446

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