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In this paper we present histopathological breast cancer image analysis, feature extraction, and their clustering into benign and malignant. We used six methods for feature extraction, PCA for dimensionality reduction, ensamble clustering and semi-supervised learning were evaluated and adjusted rand index was used as an external validation measure.

EVALUACIJA PERFORMANSI KONSENZUS KLASTEROVANJA NAD HISTOPATOLOŠKIM SLIKAMA TUMORA DOJKE