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Worldwide, breast cancer is one of the most threatening killers to mid-aged women. The diagnosis of breast cancer aims to classify spotted breast tumor to be Benign or Malignant. With recent developments in data mining technique, new model structures and algorithms are helping medical workers greatly in improving classification accuracy. In this study, a model is proposed combining ensemble method and imbalanced learning technique for the classification of breast cancer data. First, Syntheticdoi:10.11648/j.acm.20180703.20 fatcat:f5zdb647azcbpc6kq465grb4nq