Description: Kuschner论文，贝叶斯网络方法在质谱数据特征选择。其中关于机器学习中贝叶斯分类器部分有完整原理分析，可以用于认知无线电网络的频谱感知等新领域。含有matlab程序大于100页，子函数很多。-Kuschner paper, Bayesian network methods of feature selection in mass spectrometry data. One of the Bayes classifier machine learning part of a complete theory analysis, can be used for spectrum sensing cognitive radio networks and other new fields. Matlab program contains more than 100 pages, Functions a lot. Platform: |
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Author:孟庆民 |
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Description: 概率神经网络(Probabilistic Neural Network)是由D.F.Speeht博士在1989年首先提出，是径向基网络的一个分支，属于前馈网络的一种。它具有如下优点：学习过程简单、训练速度快；分类更准确，容错性好等。从本质上说，它属于一种有监督的网络分类器，基于贝叶斯最小风险准则。(The rate neural network, first proposed in 1989, is a branch of the RBF network and is one of the feedforward networks. It has the following advantages: the learning process is simple, the training speed is fast, the classification is more accurate, the fault tolerance is good, and so on. In essence, it belongs to a supervised network classifier based on Bayesian minimum risk criteria.) Platform: |
Size: 46080 |
Author:哼哼1214
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