Abstract

This study work presents a systematic analysis of various features of the higher grade school public examination results data in the state of Tamil Nadu, India through different data mining classification algorithms to predict the performance of Schools. Nowadays the parents always targets to select the right city, school and factors which contributes to the success of the results in schools of their children. There could be possible effects of factors such as Ethnic mix, Medium of study, geography could make a difference in results. The proposed work would focus on two fold factors namely Machine Learning algorithms to predict School performance with satisfying accuracy and to evaluate the data mining technique which would give better accuracy of the learning algorithms. It was found that there exist some apparent and some less noticeable attributes that demonstrate a strong correlation with student performance. Data were collected through the credible source data preparation and correlation analysis. The findings revealed that the public examinations results data was a very helpful predictor of performance of school in order to improve the result with maximum level and also improved the overall accuracy with the help of Adaboost technique.

Keywords:

Educational data mining , prediction of school performance , public examination , random forest,

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Competing interests

The authors have no competing interests.

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