A major cause of unreliable models is excessive model complexity, and regularization methods aim to improve the predictive performance by adequately constraining model complexity.
To address this issue, an efficient nonlinear mapping method called the constructive polynomial mapping (CPM) is utilized in lieu of the radial basis kernel function to avoid the excessive modeling redundancy.
Other methods treat these networks in a global manner (instead of fitting logic functions node by node) borrowing ideas from optimization and machine learning to avoid excessive model complexity (Bonneau et al., 2006; Saez-Rodriguez et al., 2009).
According to the excessive response model survived tumor cells may obtain higher capability to deal with additional ROS-generating insults and higher dose of irradiation, which makes them harder to be killed by the immune system.
The use of excessive variables in model development may cause model over-fitting (i.e., two or more different variables in the model account for the same variability in the results, which may result in spurious results).
The advantage of this method is the reduction of excessive switch between models and also decrement of the computational complexity in the controller bank that can lead to performance improvement of the control system.
The highly customised production had led to an excessive diversity of models, which made spare part supply difficult.
This indicates that, in line with the aforementioned animal models, excessive apoptosis generates vacant cell compartments that subsequently are repopulated by more competitive HSCs.
However existing energy modelling tools fail to meet many of the needs to manage this process, due to the excessive complexity of modelling frameworks.
Both books display excessive enthusiasm for model numbers.
To model excessive nFGFR1 signaling, NPC cultures were transfected with constitutively active nFGFR1 SP-/NLS) anFGFR1 SP-/NLSh and/BDNF/GDNF.
