Heart Disease Prediction

  • Authors

    • S Vinothini
    • Ishaan Singh
    • Sujaya Pradhan
    • Vipul Sharma
    2018-07-20
    https://doi.org/10.14419/ijet.v7i3.12.16494
  • .

  • Abstract

    Machine learning algorithm are used to produce new pattern from compound data set. To cluster the patient heart condition to check whether his /her heart normal or stressed or highly stressed k-means clustering algorithm is applied on the patient dataset. From  the results of clustering ,it is hard to elucidate and to obtain the required conclusion from these clusters. Hence another algorithm, the decision tree, is used for the exposition of the clusters of . In this work, integration of decision tree with the help of k-means algorithm is aimed. Another learning technique such as SVM and Logistics regression is used. Heart disease prediction results from SVM and Logistics regression were compared.

     

  • References

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  • How to Cite

    Vinothini, S., Singh, I., Pradhan, S., & Sharma, V. (2018). Heart Disease Prediction. International Journal of Engineering & Technology, 7(3.12), 750-753. https://doi.org/10.14419/ijet.v7i3.12.16494

    Received date: 2018-07-29

    Accepted date: 2018-07-29

    Published date: 2018-07-20