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[https://deepai.org/machine-learning-glossary-and-terms/affinity-matrix Source : DeepAI.org ] | |||
[ | [http://lagis-vi.univ-lille1.fr/~lm/classpec/reunion_23_03_07/WeissImage_nv.pdf Source : Université de Lille ] | ||
[https://fr.wikipedia.org/wiki/Matrice_de_similarit%C3%A9 Source : Wikipédia ] | |||
[[Catégorie:DeepAI.org]] | |||
[[Catégorie:vocabulary]] | [[Catégorie:vocabulary]] |
Version du 6 mai 2021 à 13:59
Définition
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Français
matrice d'affinité
matrice de similarité
matrice de substitution
Anglais
Affinity Matrix
An Affinity Matrix, also called a Similarity Matrix, is an essential statistical technique used to organize the mutual similarities between a set of data points. Similarity is similar to distance, however, it does not satisfy the properties of a metric, two points that are the same will have a similarity score of 1, whereas computing the metric will result in zero. Typical examples of similarity measures are the cosine similarity and the Jaccard similarity. These similarity measures can be interpreted as the probability that that two points are related. hor example, if two data points have coordinates that are close, then their cosine similarity score ( or respective “affinity” score) will be much closer to 1 than two data points with a lot of space between them.
Contributeurs: Claire Gorjux, Imane Meziani, wiki