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In this paper, we proposed context-based probability neural network (CPNN) classifiers for solving a medical decision making problems. The concept of “contexts” coming from the clustering research area is explored here to construct the second layer of probability neural network classifiers. Furthermore, genetic algorithm is used to optimize the structure parameters when designing the proposed CPNN...
This paper concerns the design of classifiers for medical decision making, and proposes a novel probabilistic neural network classifier with the assistance of a genetic algorithm. Unlike the conventional probabilistic neural networks that use all patterns in data sets as hidden nodes, the proposed neural network adopts some centers through clustering algorithms and the output of data set as the hidden...
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