Diagnosis of Breast Tumor Using SVM-KNN Classifier
Rong Li, Yuan Sun · 2010
Support vector machine (SVM) and K-Nearest Neighbor (KNN) classifier is a combined classifying method, which has excellent performance for various applications. The purpose of this study is to examine the performance of the SVM-KNN classifier on the diagnosis of breast cancer using tumor dataset. The objective is to classify a tumor as either benign or malignant based on cell descriptions gathered by microscopic examination. The classification performance of SVM-KNN classifier is evaluated and compared to the one that obtained by support vector machine. Experimental results show that SVM-KNN model has achieved a remarkable performance with 98.06% classification accuracy on testing subset.