Naive Bayes algorithm is an effective simple classification algorithm. Since its conditional independence assumption is not always true in real life,its classification performance is affected to some extent.
朴素贝叶斯算法是一种简单而高效的分类算法,但其条件独立性假设并不符合客观实际,这在某种程度上影响了它的分类性能。
参考来源 - 基于Rough Set的加权朴素贝叶斯分类算法 in C·2,447,543篇论文数据，部分数据来源于NoteExpress
朴素贝叶斯算法，可使用对象进行分类，通常是二进制类。
Naive Bayes is an algorithm that can be used to classify objects into usually binary categories.
文章以朴素贝叶斯算法为例，详细描述了性能预测模块的构建过程。
This paper takes Naive Bayes Classifier as an illustration to describe how to construct a prediction module in detail.
实验结果表明，与传统的朴素贝叶斯算法相比，该方法具有更好的性能。
The experimental results show that this algorithm has better performance when compared with traditional naive Bayesian algorithm.
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