June 11, 2024, 4:46 a.m. | Vahid MohammadZadeh Eivaghi, Mahdi Aliyari Shoorehdeli

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.05395v1 Announce Type: new
Abstract: The Fisher Information Matrix (FIM) provides a way for quantifying the information content of an observable random variable concerning unknown parameters within a model that characterizes the variable. When parameters in a model are directly linked to individual features, the diagonal elements of the FIM can signify the relative importance of each feature. However, in scenarios where feature interactions may exist, a comprehensive exploration of the full FIM is necessary rather than focusing solely on …

abstract arxiv cs.lg cs.sy dynamic eess.sy elements features fisher identification importance information matrix observable parameters random the information type

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