Predicting Thryroid disease using Machine learning methods

Authors

  • Ayisha khanum
  • Chethan M S Sridevi institute of technology and management, Tumkur

DOI:

https://doi.org/10.5281/zenodo.5219586

Keywords:

Thyroid, Machine Learning, Hypothyroidism, hyperthyroidism, Prediction

Abstract

Hypothyroidism or hyperthyroidism is a major disease in India which arises due to malfunctioning of thyroid hormones. Medical industry has enormous quantity of data, but the bulk of this data is not processed. For proper diagnosis data must be processed accurately. For accurate processing intelligent Machine Learning techniques are widely used. In this paper an attempt is made to analyze Logistic regression andSupport Vector Machine (SVM) for multiclass classification of thyroid dataset.Performance of these techniques ison basis of Precision, Recall, F measure, ROC, RMS Error and accuracy. Our analysis shows that logistic regression is more efficientthanSVM for multiclass classification of thyroid dataset.

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Published

2021-08-19

How to Cite

Ayisha khanum, & Chethan M S. (2021). Predicting Thryroid disease using Machine learning methods. International Journal of Advanced Scientific Innovation, 2(3), 1-4. https://doi.org/10.5281/zenodo.5219586