A Novel Medical Prognosis System for Breast Cancer

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Book Chapter

Publication Date



Computing Sciences and Computer Engineering


The availability of huge variety of medical dataset coming from different sources is boon for automatic medical prognosis system. Breast cancer or breast carcinoma is one of the deadly diseases of modern times. Here in this paper, we emphasize on exploring unsupervised learning techniques. The objectives of this paper are to analyze the breast cancer dataset using different clustering methods to understand the correlations of the attributes present in the dataset and then investigate with different algorithm like random forest (RF), support vector machine (SVM), multilayer perceptron (MLP) and J48 to get the best model for our prediction and classification. So, we proposed a novel medical prognosis system (NMPS) which is an ensemble learning model combines all these algorithms and gives all possible results stated above in the purview of unsupervised learning classification with different clustering techniques.

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