Moderate Step Over Sensitive Move Towards Mental Stress
P. Indhumathi1, K.Rajeswari2
1P. Indhumathi*, Research Scholar, Department of Computer Science, Tirppur Kumaran College for Women, Tirppur, Tamil Nadu, India
2Dr. K.Rajeswari, Associate Professor, Department of Computer Science, Tirppur Kumaran College for Women, Tirppur, Tamil Nadu, India.
Manuscript received on November 02, 2019. | Revised Manuscript received on November 05, 2019. | Manuscript published on November 30, 2019. | PP: 6-10 | Volume-9 Issue-4, November 2019. | Retrieval Number: C3307099319/2019©BEIESP | DOI: 10.35940/ijsce.C3307.109119
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© The Authors. Published By: 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: Data classification study is applied in a profound manner to find some statistical classifier to analyze the higher order and lower order priors, like a hood to perform the posterior using Bayesian classifiers. The rough set approaches planned with functional and to determine the existence of the attribute with the level to correlation among them. Approximations towards the set of some logical factors were filtered towards to detect the mental stress through data collection mainly from the working people sector. Significant analyses to quantify the features of mental stress in various diseases cataloging manner with its technical aspects with its classification types based on the class value. As a proposed system of suggested hypothesis planned to predict the classifier model to reduce the stress dependency for the working people as much as possible in a smoother way.
Keywords: Bayesian classifiers , Data Exploration, Decision tress , Classification, Mental Stress, Rough set Approach