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Hybrid Machine Learning Classification Technique for Improve Accuracy of Heart Disease Prediction

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  • M. Poojitha
  • Srinivasanjagannathan

Abstract

Human looks are an important way to convey emotions. In the field of PC vision, the programmed examination of these implicit opinions has been a fascinating and challenging endeavor with applications in a variety of fields, including brain research, product promotion, process robotization, and so on. This task has been hard because there are so many different ways people express their emotions through expression. Already, different strategies for AI, like Irregular timberland and SVM, were utilized to utilize changed pictures over completely to anticipate the opinion. In many areas of research, including PC vision, deep learning has been crucial to making progress. We use a model based on a convolutional neural network (CNN) to detect facial sentiment. For testing and training, the FER-2013 public dataset is utilized.

Suggested Citation

  • M. Poojitha & Srinivasanjagannathan, 2023. "Hybrid Machine Learning Classification Technique for Improve Accuracy of Heart Disease Prediction," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 9(4), pages 178-183, August.
    • Handle: RePEc:jbh:ijsrcs:v9:y2023:i4:id:hcseit2390251
    Note: Article URL: https://ijsrcseit.com/CSEIT2390251
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