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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...
Cancer diagnosis is generally the process of using some form of physical or genetic tests or exams, usually referred as patient data, to detect the disease. One of the main problems with cancer diagnosis systems is the lack of labeled data, as well as the difficulties of labeling pre-existing unlabeled data. Thus, there is a growing interest in exploring the use of unlabeled data as a way to improve...
Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. As a result, machine learning is frequently used in cancer diagnosis and detection. In this paper, support vector machines, K-nearest...
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