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  "Description": "An introduction to a couple of novel predictive variable\nselection methods for generalised boosted regression modeling\n(gbm). They are based on various variable influence methods\n(i.e., relative variable influence (RVI) and knowledge informed\nRVI (i.e., KIRVI, and KIRVI2)) that adopted similar ideas as\nAVI, KIAVI and KIAVI2 in the 'steprf' package, and also based\non predictive accuracy in stepwise algorithms. For details of\nthe variable selection methods, please see: Li, J., Siwabessy,\nJ., Huang, Z. and Nichol, S. (2019)\n<doi:10.3390/geosciences9040180>. Li, J., Alvarez, B.,\nSiwabessy, J., Tran, M., Huang, Z., Przeslawski, R., Radke, L.,\nHoward, F., Nichol, S. (2017). <DOI:\n10.13140/RG.2.2.27686.22085>.",
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