Comparison of different classifier models to predict a student's performance in Mathematics.
This data approach student achievement in secondary education of two Portuguese schools. The data attributes include student grades, demographic, social and school related features, and it was collected by using school reports and questionnaires. The dataset is provided regarding the performance in Mathematics. This experiment is based on the binary classification and the models used by Cortez, but now build with AzureML. His original paper can be found here: http://www3.dsi.uminho.pt/pcortez/student.pdf Source: P. Cortez and A. Silva. Using Data Mining to Predict Secondary School Student Performance. In A. Brito and J. Teixeira Eds., Proceedings of 5th FUture BUsiness TEChnology Conference (FUBUTEC 2008) pp. 5-12, Porto, Portugal, April, 2008, EUROSIS, ISBN 978-9077381-39-7. The data is available on the UCI Machine Learning Repository: http://archive.ics.uci.edu/ml/datasets/Student+Performance