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Interpretable Machine Learning to understand Participant Evolution in Longitudinal Cohort Study Data for SHIP dataset

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logitudinal_cohort_study

Interpretable Machine Learning to understand Participant Evolution in Longitudinal Cohort Study Data

Tasks

Design and implementation of a visual exploration tool which would include features to :

  • Measure the influence of each evolution feature on the predicted class.
  • Evaluate the merit of an evolution feature towards classification accuracy.
  • Analyse the minimal change in the participant such that the predicted class label changes.
  • Identify the minimal set of evolution features that would result in better predictive performance.

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Interpretable Machine Learning to understand Participant Evolution in Longitudinal Cohort Study Data for SHIP dataset

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