Extreme phenotype sampling improves lasso and random forest marker selection for complex traits
Most attempts to fit a supervised machine learning (ML) model in bioinformatics try to predict
the full range of trait or response values. While such prediction tasks effectively capture the …
the full range of trait or response values. While such prediction tasks effectively capture the …
[引用][C] Extreme Phenotype Sampling Improves LASSO and Random Forest Marker Selection for Complex Traits
C John, W Muchero, S Emrich - cbi.ornl.gov
[PDF][PDF] Extreme phenotype sampling improves lasso and random forest marker selection for complex traits
C John, W Muchero, S Emrich - 2020 IEEE International …, 2020 - drive.google.com
(ML) model in bioinformatics try to predict the full range of trait or response values. While
such prediction tasks effectively capture the entire phenotypic range of the samples, they are …
such prediction tasks effectively capture the entire phenotypic range of the samples, they are …
Extreme Phenotype Sampling Improves LASSO and Random Forest Marker Selection for Complex Traits
C John, W Muchero, S Emrich - 2020 IEEE International Conference …, 2020 - computer.org
Most attempts to fit a supervised machine learning (ML) model in bioinformatics try to predict
the full range of trait or response values. While such prediction tasks effectively capture the …
the full range of trait or response values. While such prediction tasks effectively capture the …