Aggrandizing the Accuracy of Body Fat Percentage by Stratification using Decision Tree
J. Grace Hannah1, D. Gladis2

1J. Grace HannahResearch Scholar, Department of Computer Science, Presidency College, Affiliated to The University of Madras, Chennai, India.
2Dr. D. Gladis, Principal, Bharathi Women’s College, Chennai, India.

Manuscript received on 22 August 2019. | Revised Manuscript received on 02 September 2019. | Manuscript published on 30 September 2019. | PP: 1883-1886 | Volume-8 Issue-11, September 2019. | Retrieval Number: K20870981119/2019©BEIESP | DOI: 10.35940/ijitee.K2087.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Bariatrics is the branch of science which deals with obesity and its related surgical procedures. A person’s physical indolence, unhealthy food habits and genetic constitution emanates as the fons et origo of health gremlins. Multifaceted indagations have been worked on the diverse and heterogenous obstinate concerns caused due to obesity. Anatomization of body fat percentage has become a rudimentary regimen for every individual to be done in a fastidious manner. The whilom work anent body fat percentage entailed Body Mass Index (BMI) with respect to age and gender of a person. The anatomical conformation of an individual unraveling the fat constitution and the muscle tissue composition is not computationally enumerated using BMI. Thus, the formula using BMI dempers the veracity for a person having more muscle mass than fat mass and speciously vitiates the fat percentage of that person. The proposed novel formula is analyzed by cross-validated classification model using decision tree, and is effectuated by implementing information gain. This accentuates the coherence, efficacy and accuracy of the derived body fat percentage for a person. The Ethical Committee approval for this study has been obtained from the Institutional Ethics Committee, Madras Medical College, Chennai. The empirical study has been simulated using Matlab and the results have been successfully acquired in the GUI mode.
Keywords: Obesity, Body Fat Percentage, BMI, Decision Tree, Matlab GUI
Scope of the Article: