Initial state perturbations as a validation method for data-driven fuzzy models of cellular networks.
Journal:
BMC bioinformatics
Published Date:
Sep 21, 2018
Abstract
BACKGROUND: Data-driven methods that automatically learn relations between attributes from given data are a popular tool for building mathematical models in computational biology. Since measurements are prone to errors, approaches dealing with uncertain data are especially suitable for this task. Fuzzy models are one such approach, but they contain a large amount of parameters and are thus susceptible to over-fitting. Validation methods that help detect over-fitting are therefore needed to eliminate inaccurate models.