LEARNABLE - определение. Что такое LEARNABLE
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Что (кто) такое LEARNABLE - определение

Learnable Evolution Model

Learnable      
·adj Such as can be learned.
Learnable evolution model         
The learnable evolution model (LEM) is a non-Darwinian methodology for evolutionary computation that employs machine learning to guide the generation of new individuals (candidate problem solutions). Unlike standard, Darwinian-type evolutionary computation methods that use random or semi-random operators for generating new individuals (such as mutations and/or recombinations), LEM employs hypothesis generation and instantiation operators.
Probably approximately correct learning         
FRAMEWORK FOR MATHEMATICAL ANALYSIS OF MACHINE LEARNING
PAC learning; PAC Learning; PAC-learning; Pac-learning; Probably approximately correct; PAC learnable; PAC-learnable; PAC learnability; PAC framework; PAC criterion; Probably Approximately Correct; PAC guarantees
In computational learning theory, probably approximately correct (PAC) learning is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant.

Википедия

Learnable evolution model

The learnable evolution model (LEM) is a non-Darwinian methodology for evolutionary computation that employs machine learning to guide the generation of new individuals (candidate problem solutions). Unlike standard, Darwinian-type evolutionary computation methods that use random or semi-random operators for generating new individuals (such as mutations and/or recombinations), LEM employs hypothesis generation and instantiation operators.

The hypothesis generation operator applies a machine learning program to induce descriptions that distinguish between high-fitness and low-fitness individuals in each consecutive population. Such descriptions delineate areas in the search space that most likely contain the desirable solutions. Subsequently the instantiation operator samples these areas to create new individuals. LEM has been modified from optimization domain to classification domain by augmented LEM with ID3 (February 2013 by M. Elemam Shehab, K. Badran, M. Zaki and Gouda I. Salama).