Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Alex Gramegna"'
Autor:
Alex Gramegna, Paolo Giudici
Publikováno v:
Frontiers in Artificial Intelligence, Vol 4 (2021)
In credit risk estimation, the most important element is obtaining a probability of default as close as possible to the effective risk. This effort quickly prompted new, powerful algorithms that reach a far higher accuracy, but at the cost of losing
Externí odkaz:
https://doaj.org/article/48d1ddd8c98f478db6baafb5bf1c3538
Autor:
Alex Gramegna, Paolo Giudici
Publikováno v:
Risks, Vol 8, Iss 4, p 137 (2020)
We propose an Explainable AI model that can be employed in order to explain why a customer buys or abandons a non-life insurance coverage. The method consists in applying similarity clustering to the Shapley values that were obtained from a highly ac
Externí odkaz:
https://doaj.org/article/7c47e5313bc849f08c9d667ec1ad33c9
Publikováno v:
Socio-Economic Planning Sciences. 87:101560
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d7c2951038547ad06ca0cf62af0d65a
https://doi.org/10.1016/j.seps.2023.101560
https://doi.org/10.1016/j.seps.2023.101560
Autor:
Alex Gramegna, Paolo Giudici
Publikováno v:
FinTech; Volume 1; Issue 1; Pages: 72-80
Feature selection is a popular topic. The main approaches to deal with it fall into the three main categories of filters, wrappers and embedded methods. Advancement in algorithms, though proving fruitful, may be not enough. We propose to integrate an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6013f0c46363fa6a0be72b2032f46ec3
Autor:
Paolo Giudici, Alex Gramegna
Publikováno v:
Frontiers in Artificial Intelligence
Frontiers in Artificial Intelligence, Vol 4 (2021)
Frontiers in Artificial Intelligence, Vol 4 (2021)
In credit risk estimation, the most important element is obtaining a probability of default as close as possible to the effective risk. This effort quickly prompted new, powerful algorithms that reach a far higher accuracy, but at the cost of losing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6006c57710c45bc1667375488aedafb0
http://europepmc.org/articles/PMC8484963
http://europepmc.org/articles/PMC8484963
Autor:
Paolo Giudici, Alex Gramegna
Publikováno v:
Risks
Volume 8
Issue 4
Risks, Vol 8, Iss 137, p 137 (2020)
Volume 8
Issue 4
Risks, Vol 8, Iss 137, p 137 (2020)
We propose an Explainable AI model that can be employed in order to explain why a customer buys or abandons a non-life insurance coverage. The method consists in applying similarity clustering to the Shapley values that were obtained from a highly ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47992e2993c9a80dfc722b0d984b81d2
https://doi.org/10.3390/risks8040137
https://doi.org/10.3390/risks8040137