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Evaluating the Performance of a Centroid-Based Probabilistic Neural Network

机译:评估基于质心的概率神经网络的性能

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In this article is proposed a technique which uses centroids together with Probabilistic Neural Network to minimize some disadvantages of this net, such as the storage space for the neural network weights and linear time complexity order with the number of training samples. In the experiments carry out the memory usage and classification time were drastically reduced. Besides, the quality of the results was also considering improved by the a priory probability, when using it with theses centroids.
机译:在本文中,提出了一种技术,该技术与概率神经网络一起使用质心来最小化该网络的一些缺点,例如神经网络权重的存储空间和具有训练样本的数量的线性时间复杂度顺序。在实验中,执行内存使用率和分类时间急剧减少。此外,当用词以质心使用时,结果的质量也在考虑到序列概率的提高。

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