Predicting Psychological Health from Childhood Essays. The UGent-IDLab CLPsych 2018 Shared Task System.
Klim Zaporojets, Lucas Sterckx, Johannes Deleu, Thomas R. DeMeester, Chris Develder · 2018
This paper describes the IDLab system submitted to Task A of the CLPsych 2018 shared task.The goal of this task is predicting psychological health of children based on language used in hand-written essays and sociodemographic control variables.Our entry uses word-and character-based features as well as lexicon-based features and features derived from the essays such as the quality of the language.We apply linear models, gradient boosting as well as neural-network based regressors (feed-forward, CNNs and RNNs) to predict scores.We then make ensembles of our best performing models using a weighted average.