• E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

  • E-ISSN:

    2454-9584

    P-ISSN

    2454-8111

    Impact Factor 2020

    5.051

    Impact Factor 2021

    5.610

INTERNATIONAL JOURNAL OF INVENTIONS IN ENGINEERING & SCIENCE TECHNOLOGY

International Peer Reviewed (Refereed), Open Access Research Journal
(By Aryavart International University, India)

Paper Details

Developing A Hand Gesture Recognition Based Integrated System To Effectively Convert ‘Sign’ To ‘Text.’

Siddharth Bhardwaj

Guru Gobind Singh Indraprastha University, New Delhi, India

57 - 61 Vol. 6, Jan-Dec, 2020
Receiving Date: 2020-10-21;    Acceptance Date: 2020-11-20;    Publication Date: 2020-11-26
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Abstract

Information mining is an interaction that arrangements with important mining data from unpleasant information. The technique for forecast investigation (PA) is executed for anticipating prospects based on current data. This exploration work is moved toward the premise of anticipating coronary illness. The coronary issue can be estimated in various stages in which pre-handling is done, credits are extricated, and grouping is performed. The half breed technique is presented based on RF and LR. The Random Forest characterization is taken to extricate the characteristics, and the order cycle is completed utilizing strategic relapse. The examination of the exhibition of the presented framework is finished as to exactness, accuracy and review. It is demonstrated that the presented framework will be given exactness roughly above 90% while anticipating coronary illness.

Keywords: Logistic Regression; Decision Tree; Heart Disease prediction; MLP; Naïve Bayes; Random Forest

    References

  1. Sellappan Palaniappan and Rafiah Awang, “Intelligent Heart Disease Prediction System using
  2. Franck Le Duff, Cristian Munteanb, Marc Cuggiaa and Philippe Mabob, “Predicting Survival Causes After Out of Hospital Cardiac Arrest using Data Mining Method”, Studies in Health Technology and Informatics, Vol. 107, No. 2, pp. 1256-1259, 2004.
  3. W.J. Frawley and G. Piatetsky-Shapiro, “Knowledge Discovery in Databases: An Overview”, AI Magazine, Vol. 13, No. 3, pp. 57-70, 1996.
  4. HeonGyu Lee, Ki Yong Noh and Keun Ho Ryu, “Mining Bio Signal Data: Coronary Artery Disease Diagnosis using Linear and Nonlinear Features of HRV”, Proceedings of International Conference on Emerging Technologies in Knowledge Discovery and Data Mining, pp. 56- 66, 2007.
  5. Kiyong Noh, HeonGyu Lee, Ho-Sun Shon, Bum Ju Lee and Keun Ho Ryu, “Associative Classification Approach for Diagnosing Cardiovascular Disease”, Intelligent Computing in Signal Processing and Pattern Recognition, Vol. 345, pp. 721-727, 2006
  6. Latha Parthiban and R. Subramanian, “Intelligent Heart Disease Prediction System using CANFIS and Genetic Algorithm”, International Journal of Biological, Biomedical and Medical Sciences, Vol. 3, No. 3, pp. 1-8, 2008.
  7. Niti Guru, Anil Dahiya and Navin Rajpal, “Decision Support System for Heart Disease Diagnosis using Neural Network”, Delhi Business Review, Vol. 8, No. 1, pp. 1-6, 2007.
  8. Anjan Nikhil Repaka, Sai Deepak Ravikanti, Ramya G Franklin, “Design And Implementing Heart Disease Prediction Using Naives Bayesian”, 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI)
  9. Aditi Gavhane, Gouthami Kokkula, Isha Pandya, Prof. Kailas Devadkar, “Prediction of Heart Disease Using Machine Learning”, 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)
  10. Aakash Chauhan, Aditya Jain, Purushottam Sharma, Vikas Deep, “Heart Disease Prediction using Evolutionary Rule Learning”, 2018, 4th International Conference on Computational Intelligence & Communication Technology (CICT)
  11. C. Sowmiya, P. Sumitra, “Analytical study of heart disease diagnosis using classification techniques”, 2017 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS)
  12. Rashmi G Saboji, “A scalable solution for heart disease prediction using classification mining technique”, 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS)
  13. Ankita Dewan, Meghna Sharma, “Prediction of heart disease using a hybrid technique in data mining classification”, 2015 2nd International Conference on Computing for Sustainable Global Development (INDIACom)
  14. Aditi Gavhane, Gouthami Kokkula, Isha Pandya, Prof. Kailas Devadkar, “Prediction of Heart Disease Using Machine Learning”, 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)
  15. M. A. Jabbar, Shirina Samreen, “Heart disease prediction system based on hidden naive bayes classifier”, 2016 International Conference on Circuits, Controls, Communications and Computing (I4C)
  16. Purushottam, Kanak Saxena, Richa Sharma, “Efficient heart disease prediction system using decision tree”, 2015, International Conference on Computing, Communication & Automation
  17. Aakash Chauhan, Aditya Jain, Purushottam Sharma, Vikas Deep, “Heart Disease Prediction using Evolutionary Rule Learning”, 2018, 4th International Conference on Computational Intelligence & Communication Technology (CICT)
  18. C. Sowmiya, P. Sumitra, “Analytical study of heart disease diagnosis using classification techniques”, 2017 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS)
  19. Rashmi G Saboji, “A scalable solution for heart disease prediction using classification mining technique”, 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS)
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