Breast Cancer Detection using Gradient Boost Ensemble Decision Tree Classifier

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Abstract

Detection of any abnormalities in the human is a big challenge faced by many of the field experts. One such challenge is to detect the Breast Cancer. The prime mottobehind in making this paper is to detect the breast cancer with the help of breast images in an advanced and appropriate way. In this study, an attempt is made in such a way by applying the combination of various existing technics in the extracted breast images for getting better result in detecting the Breast Cancer. Consequently,feature extracting images are appliedusing Light gradient boosting ensemble decision tree classifier for identifying benign and malign features of an image. As a result, the normal and abnormal breast cancer image is detected by combining above applications. Besides, classification accuracy and minimize classification time metrics are also achieved more appropriately than the existing detectingtechnics.

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Ezhilraman, S. V., Srinivasan, S., & Suseendran, G. (2019). Breast Cancer Detection using Gradient Boost Ensemble Decision Tree Classifier. International Journal of Engineering and Advanced Technology, 9(2), 2169–2173. https://doi.org/10.35940/ijeat.b3664.129219

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