E. Haripriya
In Health Care Systems to deal with the huge amount of data, Machine Learning algorithms play the vital role for earlier disease detection and prediction. In recent years, the most common issue identified in many women and men in their adolescent age was Thyroid issues. The issue once detected cannot be cured but the symptoms can be managed by proper treatment. Thyroid can be identified by the symptoms such as on thyroxine, query on thyroxine, query hypothyroid etc. Early identification and diagnosis are the basic factor for the correct treatment. In our study, the performance of the four Machine Learning Algorithms Decision Tree Classifier, Support Vector Machine, Random Forest Regressor and KNeighbors Classifier are analyzed and compared to predict the disease based on the performance metrics such as accuracy, recall and precision.
Machine Learning, Thyroid, Decision Tree, Support Vector Machine, Random Forest Regressor, KNeighbors Classifier.