Data Mining Classification on Hypo Thyroids Detection: Association Women Outnumber Men
Suwarna Gothane

Dr. Suwarna Gothane, Professor, Department of Computer Science and Engineering, MLR Institute of Technology, Hyderabad, India.
Manuscript received on February 02, 2020. | Revised Manuscript received on February 10, 2020. | Manuscript published on March 30, 2020. | PP: 601-604 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7261038620 /2020©BEIESP | DOI: 10.35940/ijrte.F7261.038620

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Abstract: Thyroid diseases are common worldwide and affecting health life. Health care is an inevitable task to be done in human life. In this paper, we have made an attempt to diagnosis hypothyroid. This paper analyzes few essential parameters affecting thyroid. Data mining acts as a solution to many thyroid healthcare problems. To overcome the problem we have come here with a novel solution approach to identify key factors affecting hypothyroid using WEKA tool 3.8. This paper presents thyroid data analysis, classification and prediction. The result of the proposed work used for the forthcoming identification to keep track on important factors affecting hypothyroid.
Keywords: Data Mining, Hypo Thyroidism, Prediction.
Scope of the Article: Data Mining.