Carta PAYBACK di Mondadori
Su Mondadori Store, con la tua carta PAYBACK ti premi ad ogni acquisto.
DR K VENKATA NAGANJANEYULU
pubblicato da
DR K VENKATA NAGANJANEYULU
Like many other classification tasks, fake job posing prediction leaves a lot of challenges to face. This paper proposed to use different data mining techniques and classification algorithm like KNN, decision tree, support vector machine, naïve bayes classifier, random forest classifier and deep neural network to predict a job post if it is real or fraudulent. We have experimented on Employment Scam Aegean Dataset (EMSCAD) containing 18000 samples. Deep neural network as a classifier, performs great for this classification task. We have used three dense layers for this deep neural network classifier. The trained classifier shows approximately 98% classification accuracy (DNN) to predict a fraudulent job post.
Scrivi una recensione per "A Comparative Study on Fake Job Post Prediction Using Different Data mining Techniques"
Torna in cima
Leggi un estratto
dai un voto
