Comparison of Novel Recurrent Neural Network Over Artificial Neural network in Predicting Email spammers with improved accuracy

Autor: Neeharika Chillakuru, Kalaiarasi S.
Jazyk: English<br />French
Rok vydání: 2023
Předmět:
Zdroj: E3S Web of Conferences, Vol 399, p 04025 (2023)
Druh dokumentu: article
ISSN: 2267-1242
DOI: 10.1051/e3sconf/202339904025
Popis: The main aim is to compare Novel Recurrent Neural Network over Artificial Neural Network in predicting Email spammers with improved accuracy. Material and Methods : This research study contains two groups namely Novel Recurrent Neural Network and Artificial Neural Network. Each group consists of a sample size of 10 and the study parameters are calculated using clincalc with preset parameters as alpha 0.8, beta 0.2 and CI as 90%. Results and Discussion : The Novel Recurrent Neural Network has the highest accuracy 97.96% when compared to Artificial Neural Network it has 93.79% accuracy in Electronic Mail spam prediction with significance value p=0.000(p
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