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Abstract

Data mining plays an important role in Health care. It really helps to predict the disease based on collated data. Diagnosis in the medical field is a complicated task that should be performed with accuracy and efficiency. A diagnosis performed by a physician for a single patient may differ significantly if the same is examined by the other physicians or by the same physicians at different times to that single patient. Now a days, automated medical analysis are used to help doctors to predict diseases at a very fast pace. Gynecological disease is addressed in this study which is neglected; it may even prove disastrous if left unattended. Sum of 626 instances with 5 attributes are used as the medical dataset for this work. Weka is built in software tool for data mining. J48 (decision tree), Navie Bayes (NB), Multilayer perception (Artificial Neural Networks), ZeroR (Rule based) and Multiclass classifier (Support Vector Machines) are the five classification algorithms used.one of the difficult task in the predicting dermatological diseases is that as there exist a large number of similar typed presentations. This paper deals with the data collected from the southern.