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Download full textAzarnoush, Bahareh; Bekki, Jennifer M.; Runger, George C.; Bernstein, Bianca L.; Atkinson, Robert K. – Journal of Educational Data Mining, 2013
Effectively grouping learners in an online environment is a highly useful task. However, datasets used in this task often have large numbers of attributes of disparate types and different scales, which traditional clustering approaches cannot handle effectively. Here, a unique dissimilarity measure based on the random forest, which handles the…
Descriptors: Online Courses, Females, Doctoral Programs, Graduate Students
