The event happenings of the future are becoming more predictable with the advancement of computer science and the integration with statistics termed under the domain of machine learning. Our project aims to use this domain to predict the performance of a human using minimum labels as attributes. As present solutions in machine learning helped humanity to predict natural events there is no accurate existing solution to predict the same for human beings. Human efficiency may include the development of an individual or the development of a team or collaboration. Making progress in a work without knowing the success rate might be a challenge as the final output may or may not give expected results. The amount of hard work engaged in a work that may fail in the future causes a great loss of time and energy. The involvement of computers integrated with the statistical models motivates and helps to predict the final output. So, we have taken the initiative to predict the future performance of a person in a more accurate and precise manner. As a base, this project aims to predictthe future performance of a student in university examinations using a machine learning algorithm by Ensembled-based Progressive Prediction.

Ensembled Based Progressive Predictor, Naive Bayes, C4.5 Classification, Performance Prediction, Future Performance.