.

ISSN 2063-5346
For urgent queries please contact : +918130348310

PREDICTING ONLINE RUMMY GAME MENTAL DISORDER CAUSED IN YOUNGSTERS USING DEEP BELIEF NETWORK COMPARED OVER SUPPORT VECTOR MACHINE WITH IMPROVED ACCURACY

Main Article Content

K.Mohan Krishna, S. Subbiah
» doi: 10.31838/ecb/2023.12.sa1.485

Abstract

Aim:Predicting online rummy game mental disorder caused in youngsters using Deep belief network compared over support vector machine with improved accuracy. Materials and Methods:The Deep belief network(N=10) and support vector machine Algorithm (N=10) these two algorithms are calculated by using 2 Groups and I have taken 20 samples for both algorithm and accuracy in this work. Results: Based on the Results Accuracy obtained in terms of accuracy is identified by Deep belief network algorithm (65.3%)over support vector machine algorithm(75.9%).Statistical significance difference between Deep belief network algorithm and support vector machine Algorithm was found to be 0.220 (p<0.05). Conclusion: The Prediction online rummy game mental disorder caused in youngsters using Deep belief network when compared with support vector machine algorithm.

Article Details