IJSRSET calls volunteers interested to contribute towards the scientific development in the field of Science, Engineering and Technology

Home > IJSRSET151535                                                     

Predicting Teens Stress According to Behavioural Activity of Parents Using Naive Bayes Classifier


Sumalatha. V, Dr. Santhi. R
  • Abstract
  • Authors
  • Keywords
  • References
  • Details
In today world, depression is a major issue for teenagers. Even depression leads to committing suicides or to addict for drugs or leads to any illegal activities etc,. For the successful future of teenagers parents should have more responsibility. In this paper the work is carried out to find the stress level of teenagers if parents are working (Father & Mother).Researchers are using classifier techniques in the field of Medical , Academic, Bioinformatics , Bio computing etc. Using the supervised learning techniques to evaluate the teenagers from the dataset given. Based on the Evaluation to find the teenagers stress level according to parentís behavior. This research will be useful to control or avoid stress factors among teenagers. We can also improve the parental care to teenagers. Using the classification algorithm we can predict the stress level of teenagers.

Sumalatha. V, Dr. Santhi. R

Supervised Learning, Classification Algorithm, Naive Bayes

  1. M. Miyakawa, "Analysis of incomplete data in a competing risks model," IEEE Trans. Rel., vol. 33, no. 4, pp. 293–296, Oct. 1984.
  2. J. S. Usher and T. J.Hodgson, "Maximum likelihood analysis of component reliability using masked system life data," Trans. Rel., vol. 37, no. 5, pp. 550–555, Dec. 1988.
  3. D. K. J. Lin, J. S.Usher, and F.M.Guess, "Exact maximum likelihood estimation using masked system data," IEEE Trans. Rel., vol. 42, no. 4, pp. 631–635, Dec. 1993.
  4. B. Reiser, I. Guttman, D. K. J. Lin, J. S. Usher, and F. M. Guess, "Bayesian inference for masked system lifetime data," Appl. Statist., vol. 44, pp. 79–90, 1995.
  5. J. O. Berger and D. Sun, "Bayesian analysis for the poly-weibull distribution," J. Amer. Statist. Assoc., vol. 88, pp. 1412–1418, 1993.
  6. C. Mukhopadhyay and A. P. Basu, "Bayesian analysis of incomplete time and cause of failure data," J. Statist. Plann. Inference, vol. 59, pp. 79–100, 1997.
  7. S. Basu, A. P. Basu, and C. Mukhopadhyay, "Bayesian analysis for masked system failure data using nonidentical weibull models," J. Statist. Plann. Inference, vol. 78, pp. 255–275, 1999.
  8. A. Sen, M. Banerjee, and S. Basu, , N. Balakrishnan and C. R. Rao, Eds., "Analysis of masked failure data under competing risks," in Handbook of Statistics. Amsterdam, The Netherlands: North-Holland, 2001, vol. 20, pp. 523–540.
  9. S. Basu, A. Sen, and M. Banerjee, "Bayesian analysis of competing risks with partially masked cause of failure," Appl. Statist., vol. 52, pp. 77–93, 2003.
  10. D. K. J. Lin and F. M. Guess, "System life data analysis with dependent partial knowledge on the exact cause of system failure," Microelectron. Rel., vol. 34, pp. 535–544, 1994.
  11. I. Guttman, D. K. J. Lin, B. Reiser, and J. S. Usher, "Dependent masking and system life data analysis: Bayesian inference for two-component systems," Lifetime Data Anal., vol. 1, pp. 87–100,1995.
  12. L. Kuo and T. E. Yang, "Bayesian reliability modeling for masked system lifetime data," Statist. Probab. Lett., vol. 47, pp. 229–241, 2000.
  13. C. Mukhopadhyay and A. P. Basu, "Masking without the symmetry assumption: A Bayesian approach," in Proc. Abstract Book 2nd Int. Conf. Math.Methods Rel., Bordeaux, France, 2000, vol. 2, pp. 784–787, Universite Victor Segalen.

Publication Details

Published in : Volume 1 | Issue 5 | September-October - 2015
Date of Publication Print ISSN Online ISSN
2015-10-25 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
173-176 IJSRSET151535   Technoscience Academy

Cite This Article

Sumalatha. V, Dr. Santhi. R, "Predicting Teens Stress According to Behavioural Activity of Parents Using Naive Bayes Classifier", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 5, pp.173-176, September-October-2015.
URL : http://ijsrset.com/IJSRSET151535.php