Tian-Tian Chang

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Clustered Microcalcification is an important signal for breast cancer in the early stages. In this paper, we propose a Multiple Kernel SVM with Group Features (GF-SVM) to tackle problems associated with heterogeneous features of clustered microcalcification and normal breast tissues in suspicious regions. Specifically, different types of features such as(More)
Support Vector Machine Clustering (SVMC) is a model-based clustering method designed primarily for solving 2-class clustering problems. In this paper, we generalize the SVMC method to multi-class clustering via two different strategies, namely One-Against-All and hierarchical clustering. We applied the resulting multi-class SVMC techniques to large scale(More)
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