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What (who) is quantification$515435$ - definition

Branching quantification; Henkin quantifier; Partially ordered quantification; Branched quantification

Quantification (machine learning)

MACHINE LEARNING PRACTICE OF SUPERVISED LEARNING

Binary quantification; Multiclass quantification; Ordinal quantification

In machine learning and data mining, quantification (variously called learning to quantify, or supervised prevalence estimation, or class prior estimation) is the task of using supervised learning in order to train models (quantifiers) that estimate the relative frequencies (also known as prevalence values) of the classes of interest in a sample of unlabelled data items.

https://en.wikipedia.org/wiki/Quantification_(machine_learning)

quantification

WIKIMEDIA DISAMBIGUATION PAGE

Quantifier (syntax); Quantification (disambiguation)

Quantification

WIKIMEDIA DISAMBIGUATION PAGE

Quantifier (syntax); Quantification (disambiguation)

·noun Modification by a reference to quantity; the introduction of the element of quantity.

Wikipedia

Branching quantifier

In logic a branching quantifier, also called a Henkin quantifier, finite partially ordered quantifier or even nonlinear quantifier, is a partial ordering

\langle Qx_{1}\dots Qx_{n}\rangle

of quantifiers for Q ∈ {∀,∃}. It is a special case of generalized quantifier. In classical logic, quantifier prefixes are linearly ordered such that the value of a variable y_m bound by a quantifier Q_m depends on the value of the variables

y₁, ..., y_m−1

bound by quantifiers

Qy₁, ..., Qy_m−1

preceding Q_m. In a logic with (finite) partially ordered quantification this is not in general the case.

Branching quantification first appeared in a 1959 conference paper of Leon Henkin. Systems of partially ordered quantification are intermediate in strength between first-order logic and second-order logic. They are being used as a basis for Hintikka's and Gabriel Sandu's independence-friendly logic.

https://en.wikipedia.org/wiki/Branching quantifier