Supervised Learning-----Naive Bayes Classification

时间 2021-01-02

标签机器学习繁體版

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Naive Bayes Classification Motivation 机器学习中反复出现的问题是需要将输入分类为一些预先存在的类。请考虑以下示例。假设我们想要对我们发现的随机水果进行分类。在这个例子中，我们有三个现有的水果类别：苹果，蓝莓和椰子。这些水果中的每一种都有三个我们关心的特征：大小，重量和颜色。该信息如图1所示。我们观察到我们发现的那块水果，并确定它的大小适中，它很重，

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1. Naive Bayes text classification
2. Navie Bayes Classification
3. [Bayes] Maximum Likelihood estimates for text classification
4. [ML] Naive Bayes for Text Classification
5. Semi-Supervised Classification With Graph Convolutional Networks
6. SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
7. Semi-Supervised Classification with Graph Convolutional Networks
8. 2 ways of using Naive Bayes classification for numeric attributes
9. 翻译--SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS
10. Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification

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