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Abstract

Data mining is the process of analyze data from different perspectives and summarizing it into useful information. Clustering is a practical unsupervised data mining task that subdivides an input data set into a desired number of subgroups so that members will have high similarity and the member of different groups have large differences. In this paper it is considered as classification algorithms for examining some mushroom, Irish and Soybean datasets. Some dataset Classified algorithm like Naive Bayes (NB), Support Vector Machine (SVM), Multilayer Perceptron (MLP). This paper it aims to consider the accuracy, sensitivity and specificity percentage to provide a desired result. While considering these algorithms it gives a comprehensive study of three grouping algorithms elements and its limitations.

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