A Literature Review on Hierarchical Naive Bayes Classifier
Ronak Chavan · International Journal for Research in Applied Science and Engineering Technology · 2019
In machine learning, classification of data has an area of many problems Naïve Bayes Model is one of the simplest and widely used models for classification.However, one of the most immanent issue with this classifier is that the attributes used to describe an instance are assumed to be independent of the given class.When this assumption is flouted then the accuracy is decreased due to interaction omission.In this review paper, we check a new model known as Hierarchical Naïve Bayes model and how it gives better and accurate results than the Naïve Bayes model.