Proaftn is a
fuzzy classification Fuzzy classification is the process of grouping elements into fuzzy sets whose membership functions are defined by the truth value of a fuzzy propositional function. A fuzzy propositional function is analogous toRussel, B. (1919). ''Introduction to ...
method that belongs to the class of
supervised learning
Supervised learning (SL) is a machine learning paradigm for problems where the available data consists of labelled examples, meaning that each data point contains features (covariates) and an associated label. The goal of supervised learning alg ...
algorithms
In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing c ...
. The
acronym
An acronym is a word or name formed from the initial components of a longer name or phrase. Acronyms are usually formed from the initial letters of words, as in ''NATO'' (''North Atlantic Treaty Organization''), but sometimes use syllables, as ...
Proaftn stands for: (PROcédure d'Affectation Floue pour la problématique du Tri Nominal), which means in English:
Fuzzy
Fuzzy or Fuzzies may refer to:
Music
* Fuzzy (band), a 1990s Boston indie pop band
* Fuzzy (composer) (born 1939), Danish composer Jens Vilhelm Pedersen
* ''Fuzzy'' (album), 1993 debut album by the Los Angeles rock group Grant Lee Buffalo
* "Fuz ...
Assignment Procedure for Nominal
Sorting
Sorting refers to ordering data in an increasing or decreasing manner according to some linear relationship among the data items.
# ordering: arranging items in a sequence ordered by some criterion;
# categorizing: grouping items with similar pro ...
.
The method enables to determine the fuzzy indifference relations by generalizing the indices (concordance and discordance) used in the
ELECTRE III method. To determine the fuzzy indifference relations, PROAFTN uses the general scheme of the
discretization
In applied mathematics, discretization is the process of transferring continuous functions, models, variables, and equations into discrete counterparts. This process is usually carried out as a first step toward making them suitable for numerical ...
technique described in, that establishes a set of pre-classified cases called a training set.
To resolve the classification problems, Proaftn proceeds by the following stages:
Stage 1. Modeling of classes: In this stage, the prototypes of the classes are conceived using the two following steps:
*Step 1. Structuring: The prototypes and their parameters (thresholds, weights, etc.) are established using the available knowledge given by the expert.
*Step 2. Validation: We use one of the two following techniques in order to validate or adjust the parameters obtained in the first step through the assignment examples known as a training set.
Direct technique: It consists in adjusting the parameters through the training set and with the expert intervention.
Indirect technique: It consists in fitting the parameters without the expert intervention as used in
machine learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence.
Machine ...
approaches.
In
multicriteria classification In multiple criteria decision aiding (MCDA), multicriteria classification (or sorting) involves problems where a finite set of alternative actions should be assigned into a predefined set of preferentially ordered categories (classes). For example, ...
problem, the indirect technique is known as ''preference disaggregation analysis''. This technique requires less cognitive effort than the former technique; it uses an automatic method to determine the optimal parameters, which minimize the classification errors.
Furthermore, several
heuristics
A heuristic (; ), or heuristic technique, is any approach to problem solving or self-discovery that employs a practical method that is not guaranteed to be optimal, perfect, or rational, but is nevertheless sufficient for reaching an immediate, ...
and
metaheuristics
In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimiza ...
were used to learn the multicriteria classification method Proaftn.
Stage 2. Assignment: After conceiving the prototypes, Proaftn proceeds to assign the new objects to specific classes.
References
{{reflist
External links
Site dedicated to the sorting problematic of MCDA
Machine learning
Statistical classification