CONFIDERAI: CONFormal Interpretable-by-Design score function for Explainable and Reliable Artificial Intelligence

被引：0

作者：

Narteni, Sara ^{[1
]}

Carlevaro, Alberto ^{[1
]}

Dabbene, Fabrizio ^{[1
]}

Muselli, Marco ^{[1
,2
]}

Mongelli, Maurizio ^{[1
]}

机构：

[1] CNR, IEIIT, I-10129 Turin, Italy

[2] Rulex Inc, Rulex Innovat Labs, I-16122 Genoa, Italy

来源：

CONFORMAL AND PROBABILISTIC PREDICTION WITH APPLICATIONS, VOL 204 | 2023年 / 204卷

关键词：

XAI; conformal safety sets; novel score function; conformal prediction;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The concept of trustworthiness has been declined in different ways in the field of artificial intelligence, but all its definitions agree on two main pillars: explainability and conformity. In this extended abstract, our aim is to give an idea on how to merge these concepts, by defining a new framework for conformal rule-based predictions. In particular, we introduce a new score function for rule-based models, that leverages on rule relevance and geometrical position of points from rule classification boundaries.

引用

页码：485 / 487

页数：3

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