Paper Title
Classification of Breast Cancer using Extreme Learning Machine: A Machine Learning Approach

Abstract - Breast Cancer being a leading cause for deaths among women has now become major health concern. In order to increase the rate of survival, early detection of tumour is most important. Mammogram image segmentation and classification plays vital role in early detection. In this paper, Extreme Learning machine (ELM) method for classification is proposed and its performance measures are evaluated on Digital Database for Screening Mammography (DDSM) dataset and other existing like Support Vector Machine (SVM), Logistic Regression (LR) and Linear Discriminant Analysis (LDA) are also implemented for comparison analysis. It is found that ELM method gives better results. Keywords - Breast Cancer, Classification, Elm, Local Binary Pattern (Lbp), Gray Level Co-Occurrence Matrix (Glcm), Gabor Features