Immune network theory

This technique was introduced by Niels Jerne (1974) and models the immune system as a dynamic network, in which cells and molecules are capable of recognizing each other. ¹

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The Artificial Immune Network can be applied in different contexts, such as:

• Clustering
• Optimization
• Classification

Package implementation

Artificial Immune Network for clustering and compression (AiNet)

AiNet is a clustering algorithm based on immune network theory that uses clonal selection and affinity maturation to compress data and identify groups ².

References

Footnotes

1. BRABAZON, Anthony; O'NEILL, Michael; MCGARRAGHY, Seán. Natural Computing Algorithms. [S. l.]: Springer Berlin Heidelberg, 2015. DOI 10.1007/978-3-662-43631-8. Disponível em: https://dx.doi.org/10.1007/978-3-662-43631-8. ↩

2. De Castro, Leandro & José, Fernando & von Zuben, Antonio Augusto. (2001). aiNet: An Artificial Immune Network for Data Analysis. Available at: https://www.researchgate.net/publication/228378350_aiNet_An_Artificial_Immune_Network_for_Data_Analysis ↩