[1] TORLAY, L., et al. 2017. Machine learning–XGBoost analysis of language networks to classify patients with epilepsy. Brain informatics, 4.3: 159.10.1007/s40708-017-0065-7
[2] ZHANG, Licheng; ZHAN, Cheng. 2017. Machine learning in rock facies classification: an application of XGBoost. In: International Geophysical Conference, Qingdao, China, 17-20 April 2017. Society of Exploration Geophysicists and Chinese Petroleum Society, p. 1371-1374.10.1190/IGC2017-351
[5] FOODY, Giles, M. 2002. Status of land cover classification accuracy assessment. Remote sensing of environment, 80.1: 185-201.10.1016/S0034-4257(01)00295-4
[6] STEHMAN, Stephen, V. 1997. Selecting and interpreting measures of thematic classification accuracy. Remote sensing of Environment, 62.1: 77-89.10.1016/S0034-4257(97)00083-7