• Corpus ID: 31856582

Assessing Gradient Boosting in the Reduction of Misclassification Error in the Prediction of Success for Actuarial Majors

@inproceedings{Olinsky2014AssessingGB,
  title={Assessing Gradient Boosting in the Reduction of Misclassification Error in the Prediction of Success for Actuarial Majors},
  author={Alan Olinsky and Kristin Kennedy and Bonnie Kennedy},
  year={2014}
}
This paper provides a relatively new technique for predicting the retention of students in an actuarial mathematics program. The authors utilize data from a previous research study. In that study, logistic regression, classification trees, and neural networks were compared. The neural networks (with prior imputation of missing data) and classification trees (with no imputation required) were most accurate. However, in this paper, we examine the use of gradient boosting to improve the accuracy… 

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