Breast cancer prediction using the isotonic separation technique
نویسندگان
چکیده
A recently developed data separation/classification method, called isotonic separation, is applied to breast cancer prediction. Two breast cancer data sets, one with clean and sufficient data and the other with insufficient data, are used for the study and the results are compared against those of decision tree induction methods, linear programming discrimination methods, learning vector quantization, support vector machines, adaptive boosting, and other methods. The experiment results show that isotonic separation is a viable and useful tool for data classification in the medical domain. 2006 Elsevier B.V. All rights reserved.
منابع مشابه
Data Classification Using the Isotonic Separation Technique: Application to Breast Cancer Prediction
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ورودعنوان ژورنال:
- European Journal of Operational Research
دوره 181 شماره
صفحات -
تاریخ انتشار 2007