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The use of linguistic rulesets is considered one of the greatest advantages that fuzzy classification systems can offer compared to non-fuzzy classification systems. This paper proposes the use of fuzzy thresholds and fuzzy quantifiers for generating linguistic rulesets from a data-driven fuzzy subsethood-based classification system. The proposed technique offers not only simplicity in the design...
The classification of breast cancer patients is of great importance in cancer diagnosis. During the last few years, many algorithms have been proposed for this task. In this paper, we review different supervised machine learning techniques for classification of a novel dataset and perform a methodological comparison of these. We used the C4.5 tree classifier, a multilayer perceptron and a naive Bayes...
Developing a treatment plan for breast cancer patient is a very complex process. In this paper, we propose a scheme of inducing fuzzy rules that characterise breast cancer treatment knowledge from data. These fuzzy rules can augment the human experts in the process of medical diagnosis to select optimal treatment for patients. The proposed machine learning scheme applies the particle swarm optimisation...
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