Français
3. Learning from data
RDF modules are developed using machine learning techniques. We distinguish here between two learning frameworks corresponding to two types of system: supervised learning and unsupervised learning (note that other frameworks exist, notably the semi-supervised framework).
We briefly present these two frameworks, then detail the elements required to learn a classification module (supervised framework) and a partitioning module (unsupervised framework).
3.1 Supervised and unsupervised settings
Supervised learning aims to design a module capable of learning an input-output association from a collection of training examples in the form of pairs (input, desired output). In the presence of an input (a particular stimulus), supervisory information...
The Ultimate Scientific and Technical Reference
This article is included in
Mathematics
This offer includes:
Knowledge Base
Updated and enriched with articles validated by our scientific committees
Services
A set of exclusive tools to complement the resources
Practical Path
Operational and didactic, to guarantee the acquisition of transversal skills
Doc & Quiz
Interactive articles with quizzes, for constructive reading
Learning from data
Distance- and neighborhood-based methods
Bibliography
The Ultimate Scientific and Technical Reference
