Aim:To implement a best efficient innovation of mental health disorder of computer users using novel Svm and linear regression. Materials and Methods: Recognition is performed by Support Vector Machine (N=10) over Linear Regression Algorithm (N=10). Sample size is calculated using GPower with pretest power as 0.8 and alpha 0.05. Result: Mean performance of Novel Support Vector Machine (90%) is high compared to Linear Regression Algorithm (80%). Significance value for performance and loss is 0.013 (p>0.05) Conclusion: the mean performance of the efficient innovation of mental health disorder of computer users using svm is better than linear regression algorithm.