M Achine L Earning R Egression a Nalysis of E Dx 2012 - 13 D Ata for I Dentifying the a Uditors Use C Ase
نویسندگان
چکیده
Predictive models are able to predict edX student grades with an accuracy error of 0.1 (10%, about one letter grade standard deviation), based on participation data. Student background variables are not useful for predicting grades. By using a combination of segmentation, random forest regression, linear transformation and application beyond the segmented data, it is possible to determine the population of the Auditors student use case, a population larger than those students completing courses with grades.
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