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Can I read Naive Bayesian Algorithm for Spam Classification Based on Random Forest Method on EtoBox?
Naive Bayesian Algorithm for Spam Classification Based on Random Forest Method by Wang, Lu; Zeng, Guohui; Huang, Bo is a Physics and Astronomy article available to read on EtoBox.
What is Naive Bayesian Algorithm for Spam Classification Based on Random Forest Method about?
## Abstract Aiming at the problem of dimensionality disasters in the spam filtering system, a spam filtering model based on content feature selection random forest algorithm is proposed. The method combines the Naïve Bayesian algorithm and effectively reduces the influence of redundant information on classification performance through feature selection filtering of Gini impurity. The improved algorithm takes advantage of decision tree integration and naive Bayesian algorithm. The experimental results show that compared with the naive Bayesian algorithm, the improved algorithm has been improved in the classification performance indicators of spam filtering, which is more feasible and effective in practical applications.
Who reads Naive Bayesian Algorithm for Spam Classification Based on Random Forest Method?
It is typically read by researchers, students, and practitioners in Physics and Astronomy.
- Author
- Wang, Lu; Zeng, Guohui; Huang, Bo
- Publisher
- Institute of Physics; IOP Publishing (ISSN 1742-6588)
- Published
- 2020
- Language
- EN
- Field
- Physics and Astronomy (Physical Sciences)