Results 131 to 140 of about 2,501,945 (313)
Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning
CoRR, 2018 v3 (Nov 2020): Fixes SD from pooled proportions in Sec 4.2 Fixes exact binomial p-value in Sec 4.4 by using max(B, C) instead of B in the sum.
openaire +2 more sources
Sub-sample Model Selection Procedures in Gets Modelling [PDF]
When the DGP is nested in the model, PcGets delivers high performance selection across different (unknown) states of nature. One of its steps involves sub-sample post-selection assessment, and here we consider its properties and investigate its practical
Hans-Martin Krolzig, David F. Hendry
core
FEBS Letters, EarlyView.An unexpected alternative interaction site for ethyl viologen was identified in formate dehydrogenase 1 from Methylorubrum extorquens. Combined mutagenesis, kinetic analysis, and docking revealed that aromatic residues near an iron–sulfur cluster enable flavin mononucleotide‐independent electron transfer, offering a framework for engineering improved ...
Eleni G. Poloniataki, Yong Hwan Kim
wiley +1 more source
FEBS Letters, EarlyView.The physical dimensions and shape of bacterial cells define the surface area available to acquire nutrients and the volume available for synthesizing proteins and DNA. Here, we use computational systems biology to decode the importance of cell geometry as a major determinant of prokaryotic phenotype, including growth rate and metabolic efficiency. This
Ross P. Carlson +6 more
wiley +1 more source
Selective Sequential Model Selection
, 2015 Many model selection algorithms produce a path of fits specifying a sequence of increasingly complex models. Given such a sequence and the data used to produce them, we consider the problem of choosing the least complex model that is not falsified by the data. Extending the selected-model tests of Fithian et al.
Fithian, William +3 more
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Semiparametric penalty function method in partially linear model selection
Model selection in nonparametric and semiparametric regression is of both theoretical and practical interest. Gao and Tong (2004) proposed a semiparametric leave–more–out cross–validation selection procedure for the choice of both the parametric and ...
Gao, Jiti, Dong, Chaohua, Tong, Howell
core
On Intercept Estimation in the Sample Selection Model [PDF]
We provide a proof of the consistency and asymptotic normality of the estimator suggested by Heckman (1990) for the intercept of a semiparametrically estimated sample selection model.
Marcia M. A. Schafgans
core
FEBS Letters, EarlyView.Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
wiley +1 more source
Random thresholds for linear model selection [PDF]
, 2005 A method is introduced to estimate the number of significant coefficients in non ordered model selection problems. The method is based on a convenient random centering of the partial sums of the ordered observations.
Lavielle, Marc, Ludeña, Carenne
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Robust Model Selection for Classification of Microarrays
, 2009 Recently, microarray-based cancer diagnosis systems have been increasingly investigated. However, cost reduction and reliability assurance of such diagnosis systems are still remaining problems in real clinical scenes.
Miki Ohira +4 more
core