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ANALYSIS ON SUSPICIOUS THYROID RECOGNITION USING ASSOCIATION RULE MINING

K.Saravana Kumar, Dr. R. Manicka Chezian

Thyroid cancer was the most common type of cancer in the country, overtaking gastric cancer for the first time in last year. This paper proposes to apply the association rule mining for suspected thyroid diseases. We apply the model of deception of set of thyroid dataset then applied apriori algorithm to generate the rules. .The rules generated are used to test the thyroid as deceptive or not. In particular we are interested in detecting thyroid about critical activities. After classification we must be able to differentiate the thyroid giving information about hyperthyroid, hypothyroid (Informative thyroid) and those acting as alerts (warnings) for the future critical activities.