J48 algorithms of machine learning for predicting user's the acceptance of an E-orientation systems

Abstract

Our research work is focused on educational guidance. For that, we propose to develop a model of E-orientation systems to understand the behavior of students towards E-orientation platforms. We rely on the Technology Acceptance Model (TAM) to position a shared qualitative questionnaire. Subsequently, we apply different Machine Learning classification algorithms to predict an acceptance model of E-orientation systems. In our study we worked with four algorithms: NaiveBayes, J48, LMT and SimpleLogistic. The simulation results that the highest classification accuracy performance is for the J48.

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