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1. On the interpretability of machine learning models and experimental feature selection in case of multicollinear data
Franc Drobnič, Andrej Kos, Matevž Pustišek, 2020, original scientific article
Keywords: interpretable machine learning, feature multicollinearity, random forests, feature selection, feature importance, greedy feature selection
2. Does machine learning offer added value vis-à-vis traditional statistics?
Montserrat González Garibay, Andrej Srakar, Tjaša Bartolj, Jože Sambt, 2022, original scientific article
Keywords: statistics, machine learning, random forests, survival analysis, retirement, time-dependent covariates