A Novel Bayes Model: Hidden Naive Bayes

By Liangxiao Jiang, Harry Zhang, Zhihua Cai. IEEE Transactions on Knowledge and Data Engineering, 2009

341 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/e9f9311e66ac1fd540d4f27455fb4767da265f05

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Bing Xue
2. Mengjie Zhang
3. Jia Wu
4. Jessa Bekker
5. Jesse Davis
6. Shahram Sarkani
7. Thomas A. Mazzuchi
8. Levent Koc

In Information Systems

1. Jessa Bekker
2. Jesse Davis
3. Jia Wu
4. Shahram Sarkani
5. Thomas A. Mazzuchi
6. Levent Koc
7. Bing Xue
8. Zhihua Cai

Citations in the corpus

• A naive Bayes probability estimation model based on self-adaptive differential evolution (2014, methodology): “Jiang et al. (2007) conducted an extensive empirical study on the performance of several commonly used Laplace-estimate and M-estimate when different Bayesian classifiers (NB (Langley et al. 1992), Tree-Augmented Naive Bayes (TAN) (Friedman et al. 1997), Averaged One-Dependence Estimators (AODE) (We”
• A Detailed Investigation and Analysis of Using Machine Learning Techniques for Intrusion Detection (2019, neutral): “Hidden Naive Bayes [92]”
• Differential evolution for filter feature selection based on information theory and feature ranking (2018, background): “In other words, the aim of feature selection is to discard features that are detrimental to the subsequent learning process [3,4] .”
• A Survey on Machine Learning Techniques for Cyber Security in the Last Decade (2020, background): “Hidden NB is an improved version to handle such kind of issues with an accuracy of 99.6% [220].”
• A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier (2012, methodology): “The HNB classifier model is applied to several datasets and shows promising results compared with the traditional Naïve Bayes and its extended methods (Jiang, Zhang, & Cai, 2009).”
• Learning from positive and unlabeled data: a survey (2018, methodology): “Averaged One-Dependence Estimator (AODE) [107] has been extended to PAODE, Hidden Naive Bayes (HNB) [43] to PHNB, and Full Bayesian network Classifier (FBC) [102] to PFBC [34].”