Evaluation of variable selection methods for random forests and omics data sets. - Frauke Degenhardt; Stephan Seifert; Silke Szymczak (Briefings Bioinform., 2019)

Surrogate minimal depth as an importance measure for variables in random forests. - Stephan Seifert; Sven Gundlach; Silke Szymczak (Bioinform., 2019)

Integrating biological knowledge and gene expression data using pathway-guided random forests: a benchmarking study. - Stephan Seifert; Sven Gundlach; Olaf Junge; Silke Szymczak; Luigi Martelli (Bioinform., 2020)

Opening the random forest black box by the analysis of the mutual impact of features. - Lucas F. Voges; Lukas C. Jarren; Stephan Seifert (CoRR, 2023)

Data sets for variable selection and relation analysis. - Stephan Seifert (UHH-FDR, 2023)

Exploitation of surrogate variables in random forests for unbiased analysis of mutual impact and importance of features. - Lucas F. Voges; Lukas C. Jarren; Stephan Seifert (Bioinform., 2023)

FTIR spectra of 11 palm-leaf manuscripts. - Lucas F. Voges; Nils Horn; Claudia Colini; Stephan Seifert (UHH-FDR, 2024)

FTIR spectra of 11 palm-leaf manuscripts. - Lucas F. Voges; Nils Horn; Claudia Colini; Stephan Seifert (UHH-FDR, 2024)

FTIR spectra of selected tsakalis cards. - Lucas F. Voges; Nils Horn; Stephan Seifert (UHH-FDR, 2024)

FTIR spectra of 19 palm-leaf manuscripts from the SUB. - Lucas F. Voges; Nils Horn; Stephan Seifert (UHH-FDR, 2024)