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Applying Representation Learning for Educational Data Mining
Milagro Teruel, Laura Alonso Alemany
Feb 18, 2016 (modified: Feb 18, 2016)ICLR 2016 workshop submissionreaders: everyone
Abstract:Educational Data Mining is an area of growing interest,
given the increase of available data and generalization of
online learning environments. In this paper we present a
first approach to integrating Representation Learning techniques
in Educational Data Mining by adding autoencoders
as a preprocessing step in a standard performance prediction
Preliminary results do not show an improvement in performance
by using autoencoders, but we expect that a fine
tuning of parameters will provide an improvement. Also, we
expect that autoencoders will be more useful combined with
different kinds of classifiers, like multilayer perceptrons.
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