Stress Prediction of Students using Machine Learning
Disha Sharma et al. Disha Sharma et al., TJPRC
2020International journal of mechanical and production engineering research and development21 citationsDOIOpen Access PDF
Abstract
forest are using and also we calculate their accuracy with the help of performance parameter like TP, FP, ROC, F-Measure etc . In this research Random forest classifier gives high accuracy of 94.73%.
Topics & Concepts
C4.5 algorithmNaive Bayes classifierMachine learningComputer sciencePerceptronArtificial intelligenceRandom forestMultilayer perceptronArtificial neural networkSupport vector machineSmart Systems and Machine LearningInternet of Things and AI