Search results
Results from the WOW.Com Content Network
Underfitting occurs when a mathematical model cannot adequately capture the underlying structure of the data. An under-fitted model is a model where some parameters or terms that would appear in a correctly specified model are missing. [2] Underfitting would occur, for example, when fitting a linear model to nonlinear data.
Homeostatic capacity refers to the capability of systems to self-stabilize in response to external forces or stressors, or more simply the capability of systems to maintain homeostasis. [ 1 ] [ 2 ] For living organisms , it is life's foundational trait, consisting of a hierarchy and network of traits endowed by nature and shaped by natural ...
The bias–variance tradeoff is a framework that incorporates the Occam's razor principle in its balance between overfitting (associated with lower bias but higher variance) and underfitting (associated with lower variance but higher bias).
Variance in egg size is an example of bet-hedging. Fitness may be maximized by producing many, small eggs and thus many offspring. However, larger eggs may help offspring survive stressful conditions.
This glossary of biology terms is a list of definitions of fundamental terms and concepts used in biology, the study of life and of living organisms.It is intended as introductory material for novices; for more specific and technical definitions from sub-disciplines and related fields, see Glossary of cell biology, Glossary of genetics, Glossary of evolutionary biology, Glossary of ecology ...
Fitting of a noisy curve by an asymmetrical peak model, with an iterative process (Gauss–Newton algorithm with variable damping factor α).Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints.
Modelling biological systems is a significant task of systems biology and mathematical biology. [a] Computational systems biology [b] [1] aims to develop and use efficient algorithms, data structures, visualization and communication tools with the goal of computer modelling of biological systems.
Allostasis emphasizes that regulation must be efficient, whereas homeostasis makes no reference to efficiency. Prediction requires the brain to: (i) collect information across all spatial and temporal scales; (ii) analyze, integrate, and decide what will be needed; (iii) exert feedforward control of all parameters.