朴素贝叶斯算法的英文
时间: 2024-06-02 21:05:57 浏览: 19
朴素贝叶斯算法(Naive Bayes algorithm)是一种基于贝叶斯定理(Bayes theorem)的简单而有效的分类算法。该算法基于一个假设,即每个特征(或属性)之间是相互独立的。这个假设被称为“朴素贝叶斯假设”(Naive Bayes assumption)。基于这个假设,朴素贝叶斯算法可以通过计算每个类别与给定数据之间的概率来确定该数据属于哪个类别。
朴素贝叶斯算法在自然语言处理、文本分类、垃圾邮件过滤等领域得到广泛应用。该算法的优点在于简单、易于实现,同时对于大规模数据集表现良好。
Naive Bayes algorithm is a simple yet effective classification algorithm based on Bayes' theorem. The algorithm is based on the assumption that each feature (or attribute) is independent of each other. This assumption is called "Naive Bayes assumption". Based on this assumption, the Naive Bayes algorithm can determine which category the data belongs to by calculating the probability between each category and the given data.
The Naive Bayes algorithm is widely used in natural language processing, text classification, spam filtering and other fields. The advantage of this algorithm is its simplicity and ease of implementation, while it performs well on large datasets.