• PARIMALA.S

Thyroid hormone produces the thyroid glands which influences the metabolic activities in our body. Abnormal production of hormone produces thyroid disorders. When the production of thyroid hormones are more then we call that as hyperthyroidism On the other hand when it is less then we call that as hypothyroidism. Data mining classification techniques plays a vital role in predicting thyroid diseases. The initial step in data mining process is that the datasets are sorted in order. The next step is you identify the patterns and relationships. In this paper a comparison analysis is done based on the thyroid dataset and classification techniques available in data mining. The classification techniques used are k nearest neighbors, Support vector machine, j48, Bagging and Naïve Bayes.

Hypothyroidism, K nearest neighbors, Support vector machine, j48, Bagging, Naïve Bayes.

"A COMPARISON ANALYSIS OF THYROID DISEASE DETECTION USING DATA MINING TECHNIQUES AND CLASSIFIERS ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 7, page no.542-546, July-2020, Available :http://www.jetir.org/papers/JETIR2007369.pdf

"A COMPARISON ANALYSIS OF THYROID DISEASE DETECTION USING DATA MINING TECHNIQUES AND CLASSIFIERS ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 7, page no. pp542-546, July-2020, Available at : http://www.jetir.org/papers/JETIR2007369.pdf