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A Comparative Study of Classification Algorithm using WEKA

S. Swetha


An important tool in many areas of research and industry is data mining. Increasingly companies & organizations are interested in applying to increase the value added by their data collections systems by using data mining tools.   Data mining is more important in the hospitality industry. As medical records systems are more standardized and commonplace, due to unanalyzed data quantity increased.  Considered the prevalence of Breast cancer among women the study is aimed at finding out the characteristics that determine the breast cancer affected person and to track the maximum number of women suffering from breast cancer with some population using WEKA tool. In this paper the classification of data will be is breast cancer patient data set of breast cancer patients is developed by collecting data from hospital repository consists of 286  instances with 10 different attributes. To classify this data and the data is evaluated by using WEKA TOOL with 10-fold cross validation and the results are to be compared.


Data Mining, Breast Cancer Dataset, Classification Algorithm WEKA Tool, Association Algorithm WEKA Tool.

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