Zobrazeno 1 - 10
of 840
pro vyhledávání: '"Graña, Manuel"'
Publikováno v:
Hybrid Artificial Intelligent Systems. HAIS 2022. Lecture Notes in Computer Science(), vol 13469
Credit scoring models are the primary instrument used by financial institutions to manage credit risk. The scarcity of research on behavioral scoring is due to the difficult data access. Financial institutions have to maintain the privacy and securit
Externí odkaz:
http://arxiv.org/abs/2301.01212
For more than a half-century, credit risk management has used credit scoring models in each of its well-defined stages to manage credit risk. Application scoring is used to decide whether to grant a credit or not, while behavioral scoring is used mai
Externí odkaz:
http://arxiv.org/abs/2204.06122
Publikováno v:
Expert Systems with Applications, 2022, 118809
The thin-file borrowers are customers for whom a creditworthiness assessment is uncertain due to their lack of credit history; many researchers have used borrowers' relationships and interactions networks in the form of graphs as an alternative data
Externí odkaz:
http://arxiv.org/abs/2111.13666
Autor:
Kerexeta-Sarriegi, Jon, García-Navarro, Teresa, Rollan-Martinez-Herrera, María, Larburu, Nekane, Espejo-Mambié, Moisés D., Beristain Iraola, Andoni, Graña, Manuel
Publikováno v:
In International Journal of Medical Informatics August 2024 188
Akademický článek
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We present Simion Zoo, a Reinforcement Learning (RL) workbench that provides a complete set of tools to design, run, and analyze the results,both statistically and visually, of RL control applications. The main features that set apart Simion Zoo from
Externí odkaz:
http://arxiv.org/abs/1904.07817
This paper presents a educational workshop in Scratch that is proposed for the active participation of undergraduate students in contexts of Artificial Intelligence. The main objective of the activity is to demystify the complexity of Artificial Inte
Externí odkaz:
http://arxiv.org/abs/1904.00296
Publikováno v:
In Expert Systems With Applications 15 May 2023 218