Explainable AI (XAI) is gaining the momentum, at now. While the idea is to apply it in different scenarios, including medicine, business analytics, genomics computing and so forth, in this paper we focus the attention on another emerging case, represented by so called smart agricolture. In this paper, we propose the application of some well-known XAI tools on top of the Crop Recommendation dataset. Our research efforts also involve the sensitivity analysis of retrieved results.

Explainable AI at Work! What Can It Do for Smart Agriculture?

Pilato Giovanni;
2022

Abstract

Explainable AI (XAI) is gaining the momentum, at now. While the idea is to apply it in different scenarios, including medicine, business analytics, genomics computing and so forth, in this paper we focus the attention on another emerging case, represented by so called smart agricolture. In this paper, we propose the application of some well-known XAI tools on top of the Crop Recommendation dataset. Our research efforts also involve the sensitivity analysis of retrieved results.
2022
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
9781665459631
Smart Agriculture
XAI
SHAP
LIME
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/463419
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