A systematic evaluation of the benefits and hazards of variable selection in latent variable regression. Part I. Search algorithm, theory and simulations
By Knut Baumann, H. Albert, M. V. Korff. 2002
83 citations recorded by the source corpus.
Subfields: Analytical Chemistry, Computational Theory and Mathematics, Spectroscopy
View Paper: https://www.semanticscholar.org/paper/4f5d940573bcef967978e63996a05d7e25834d73
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Analytical Chemistry
- Bjoern H Menze
- B. Michael Kelm
- Fred A. Hamprecht
- Peter Bachert
- Wolfgang Petrich
- Uwe Himmelreich
- Ralf Masuch
In Computational Theory and Mathematics
- Bjoern H Menze
- B. Michael Kelm
- Fred A. Hamprecht
- Peter Bachert
- Wolfgang Petrich
- Uwe Himmelreich
- Ralf Masuch
In Spectroscopy
- Bjoern H Menze
- B. Michael Kelm
- Fred A. Hamprecht
- Peter Bachert
- Wolfgang Petrich
- Uwe Himmelreich
- Ralf Masuch
Citations in the corpus
- Reliable estimation of prediction errors for QSAR models under model uncertainty using double cross-validation (2014, unknown): “The data were simulated according to reference [46].”
- A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data (2009, background): “Discarding irrelevant feature dimensions, though, raises the question of how to choose such an appropriate subset of features [ 6-8 ].”