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"Feature Selection for Polymer Informatics: Evaluating Scalability and ..."

Fiorella Cravero et al. (2020)

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DOI: 10.1021/ACS.JCIM.9B00867

access: closed

type: Journal Article

metadata version: 2024-02-05

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Fiorella Cravero, Santiago Schustik, María Jimena Martínez, Gustavo E. Vazquez, Mónica Fátima Díaz, Ignacio Ponzoni:
Feature Selection for Polymer Informatics: Evaluating Scalability and Robustness of the FS4RVDD Algorithm Using Synthetic Polydisperse Data Sets. J. Chem. Inf. Model. 60(2): 592-603 (2020)

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