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In a Bayesian network, the Markov boundary of node A includes its parents, children and the other parents of all of its children.. In statistics and machine learning, when one wants to infer a random variable with a set of variables, usually a subset is enough, and other variables are useless.
The entity–control–boundary (ECB), or entity–boundary–control (EBC), or boundary–control–entity (BCE) is an architectural pattern used in use-case–driven object-oriented programming that structures the classes composing high-level object-oriented source code according to their responsibilities in the use-case realization.
Decision boundaries are not always clear cut. That is, the transition from one class in the feature space to another is not discontinuous, but gradual. This effect is common in fuzzy logic based classification algorithms, where membership in one class or another is ambiguous. Decision boundaries can be approximations of optimal stopping boundaries.
Algorithms of this nature use statistical inference to find the best class for a given instance. Unlike other algorithms, which simply output a "best" class, probabilistic algorithms output a probability of the instance being a member of each of the possible classes. The best class is normally then selected as the one with the highest probability.
A classification model (classifier or diagnosis [7]) is a mapping of instances between certain classes/groups.Because the classifier or diagnosis result can be an arbitrary real value (continuous output), the classifier boundary between classes must be determined by a threshold value (for instance, to determine whether a person has hypertension based on a blood pressure measure).
In the statistical theory of the design of experiments, blocking is the arranging of experimental units that are similar to one another in groups (blocks) based on one or more variables.
In mathematics, the Dirichlet boundary condition is imposed on an ordinary or partial differential equation, such that the values that the solution takes along the boundary of the domain are fixed.
The points plotted as part of an ogive are the upper class limit and the corresponding cumulative absolute frequency [2] or cumulative relative frequency. The ogive for the normal distribution (on one side of the mean) resembles (one side of) an Arabesque or ogival arch, which is likely the origin of its name.