Categories
- DATA SCIENCE / AI
- AFIR / ERM / RISK
- ASTIN / NON-LIFE
- BANKING / FINANCE
- DIVERSITY & INCLUSION
- EDUCATION
- HEALTH
- IACA / CONSULTING
- LIFE
- PENSIONS
- PROFESSIONALISM
- THOUGHT LEADERSHIP
- MISC
ICA LIVE: Workshop "Diversity of Thought #14
Italian National Actuarial Congress 2023 - Plenary Session with Frank Schiller
Italian National Actuarial Congress 2023 - Parallel Session on "Science in the Knowledge"
Italian National Actuarial Congress 2023 - Parallel Session with Lutz Wilhelmy, Daniela Martini and International Panelists
Italian National Actuarial Congress 2023 - Parallel Session with Kartina Thompson, Paola Scarabotto and International Panelists
117 views
0 comments
0 likes
0 favorites
IAA1
Using machine learning (AI) model interpretation techniques, feature importance can be calculated. However, with conventional AI, feature importance variation significantly each time it is calculated, making comparisons difficult. In order to make use of this feature importance, the recently introduced TabNet model is used to capture the variation in feature importance.
0 Comments
There are no comments yet. Add a comment.