PREDICTING THE STABILITY OF CLAY MINERALS USING XGBOOST MACHINE LEARNING: EFFICIENCY AND ACCURACY THROUGH COMPOSITION DESCRIPTORS

PREDICTING THE STABILITY OF CLAY MINERALS USING XGBOOST MACHINE LEARNING: EFFICIENCY AND ACCURACY THROUGH COMPOSITION DESCRIPTORS

Clay minerals are materials that have various benefits, particularly in their swelling properties and cation exchange capacity. These materials have diverse compositional variations, each resulting in different properties. With the advancement of Ab initio computational methods such as Density Fu...

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Bibliographic Details
Main Author:	M. N. F. Syamsul, Andi
Format:	Theses
Language:	Indonesia
Online Access:	https://digilib.itb.ac.id/gdl/view/81557
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Institut Teknologi Bandung
Language:	Indonesia

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