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

The main aim is to compare Novel Recurrent Neural Network over Artificial in predicting Email spammers with improved accuracy. Material and Methods : This research study contains two groups namely Network. Each group consists of a sample size 10 the parameters are calculated using clincalc preset as alpha 0.8, beta 0.2 CI 90%. Results Discussion has highest accuracy 97.96% when compared it 93.79% Electronic Mail spam prediction significance value p=0.000(p<0.05) that significantly better. G-power 80%. When used predictor for electronic mail, performance analysis outperforms best results than performance.