Salary Prediction in It Job Market - M, Navyashree; MK, Navyashree; GR, Pooja; M, Neetu; Biradar, Arun (International Journal of Computer Sciences and Engineering, 2025)
In this study, Random Forest Regression machine learning rule is applied to predict salary levels of individuals supported their years of expertise. Random forest regression is employed since it gave higher accuracy compared to decision tree regression and Support Vector Regression classifier. Choosing the foremost effective machine learning rule so as to unravel the problems of classification and prediction of data is the most vital part of machine learning which depends on dataset likewise. The predictive accuracy of the Random forest regression on test data is 97%, while the accuracy of Decision tree regression and Support Vector Regression is 85% and 90% respectively. The model has been used on the training data to predict dependent variables and to extract features with highest impact on salary prediction.