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Machine learning with High-Cardinality categorical features in actuarial applications
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Section: Articles
Title: Machine learning with High-Cardinality categorical features in actuarial applications / Benjamin Avanzi [et al.]
Notes: Sumario: High-cardinality categorical features are pervasive in actuarial data (e.g., occupation in commercial property insurance). Standard categorical encoding methods like one-hot encoding are inadequate in these settingsRelated records: En: Astin bulletin. - Belgium : ASTIN and AFIR Sections of the International Actuarial Association = ISSN 0515-0361. - 15/05/2024 Volumen 54 Número 2 - mayo 2024 , p.213-238Materia / lugar / evento: Ciencias Actuariales y Financieras ‌Machine learning ‌Actuarios ‌Otros autores: Avanzi, Benjamin ‌
Other categories: 6
Rights: In Copyright (InC)
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