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Research on Nave Bayesian Classifier s independence assumption;

朴素贝叶斯分类器的独立性假设研究

Node-State independence assumption can provide a more tractable solution to delay constrained routing, especially when state information is Probability Density Function (PDF) of delay at each node.

然后,基于独立性假设,用相应链路延时概率密度函数的卷积计算这15条路径延时的概率密度函数。

There is an "independence hypothesis" in Bayesian classifier method:examples of the emergence of each attribute are independent from the examples of other attributes appear,the practical application of such conditions are not easily satisfied because the special version of the related characters may have new meaning in a special text.

朴素贝叶斯分类(naive Bayes)有一个“独立性假设”:给定一个实例的类标签,实例中的每个属性的出现都独立于实例中其他属性的出现,而在实际应用中这种条件并不易满足,另外由于文本的特殊性,相关的特征项可能会产生新的语义信息。