« Matrice d'affinité » : différence entre les versions


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[https://deepai.org/machine-learning-glossary-and-terms/affinity-matrix Source : DeepAI.org ]
[https://deepai.org/machine-learning-glossary-and-terms/affinity-matrix Source : DeepAI.org ]
[[Catégorie:DeepAI.org]]


[[Catégorie:vocabulary]]
[[Catégorie:vocabulary]]

Version du 15 décembre 2020 à 18:11

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Définition

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Français

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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.



Source : DeepAI.org

Contributeurs: Claire Gorjux, Imane Meziani, wiki