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<i>LGB-Stack</i>: Stacked Generalization with <i>LightGBM</i> for Highly Accurate Predictions of Polymer Bandgap

Kai Leong Goh, Atsushi Goto, Yunpeng Lu

2022ACS Omega15 citationsDOIOpen Access PDF

Abstract

at the train/test split ratio of 80/20 were 0.92 and 0.41, respectively. The accuracy scores further improved to 0.94 and 0.34, respectively, when the train/test split ratio of 95/5 was used.

Topics & Concepts

Stack (abstract data type)GeneralizationMaterials sciencePolymerOptoelectronicsComputer scienceMathematicsComposite materialMathematical analysisProgramming languageMachine Learning in Materials ScienceCCD and CMOS Imaging SensorsNeural Networks and Applications
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