Results 21 to 30 of about 4,929,720 (302)
Heatmap Regression via Randomized Rounding [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 To appear in ...
Baosheng Yu, Dacheng Tao
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Random-effects ML regression results.
, 2022 Random-effects ML regression results.
Samuel Nduati Kariuki (12575030) +2 more
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Random Design Analysis of Ridge Regression [PDF]
Foundations of Computational Mathematics, 2014 This work gives a simultaneous analysis of both the ordinary least squares estimator and the ridge regression estimator in the random design setting under mild assumptions on the covariate/response distributions. In particular, the analysis provides sharp results on the ``out-of-sample'' prediction error, as opposed to the ``in-sample'' (fixed design ...
Hsu, Daniel +2 more
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Quantile regression under random censoring [PDF]
Journal of Econometrics, 2002 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Honoré, B, Khan, S, Powell, JL
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Inclusion of bioclimatic variables in genetic evaluations of dairy cattle [PDF]
Animal Bioscience, 2021 Objective Considering the importance of dairy farming and the negative effects of heat stress, more tolerant genotypes need to be identified. The objective of this study was to investigate the effect of heat stress via temperature-humidity index (THI ...
Renata Negri +6 more
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Austral Journal of Veterinary Sciences, 2020 In dairy cattle, genetic selection for milk yield was generally based on 305 days lactation records that were calculated from available monthly test-day milk yield records.
Héctor Uribe, Felipe Lembeye
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LOGISTIC REGRESSION WITH RANDOM COEFFICIENTS [PDF]
ETS Research Report Series, 1993 ABSTRACTAn approximation to the likelihood for the generalized linear models with random coefficients is derived and is the basis for an approximate Fisher scoring algorithm. The method is illustrated on the logistic regression model for one‐way classification, but it has an extension to the class of generalized linear models and to more complex data ...
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Predicting equity market price impact with performance weighted ensembles of random forests [PDF]
, 2014 For many players in financial markets, the price impact of their trading activity represents a large proportion of their transaction costs. This paper proposes a novel machine learning method for predicting the price impact of order book events ...
Enrico Gerding +5 more
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Genomic and phenotypic selection indices for decreased birth weight, shortening fattening period, and regulating total weight gain in beef cattle [PDF]
Animal BioscienceObjective This study aimed to develop genomic and phenotypic indices for beef cattle selection that afford progeny with reduced birth weight and fattening period.
Kenji Togashi +6 more
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Random Feature Selection Using Random Subspace Logistic Regression
Expert Systems with Applications, 2022 Feature selection becomes a prominent method in the big data era. The logistic regression model is a wrapper method that provides better classification or prediction accuracy but it is computationally expensive. In this study, we propose the random subspace logistic regression where features are randomly selected through bootstrap cycles.
Nuttanan Wichitaksorn +2 more
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