Results 31 to 40 of about 3,727,733 (308)
Extreme Gradient Boosting Combined with Conformal Predictors for Informative Solubility Estimation
Molecules, 2023 We used the extreme gradient boosting (XGB) algorithm to predict the experimental solubility of chemical compounds in water and organic solvents and to select significant molecular descriptors.
Ozren Jovic, Rabah Mouras
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Beyond Support in Two-Stage Variable Selection [PDF]
, 2015 Numerous variable selection methods rely on a two-stage procedure, where a sparsity-inducing penalty is used in the first stage to predict the support, which is then conveyed to the second stage for estimation or inference purposes.
Ambroise, Christophe +3 more
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Feature Selection based on the Local Lift Dependence Scale
Entropy, 2018 This paper uses a classical approach to feature selection: minimization of a cost function applied on estimated joint distributions. However, in this new formulation, the optimization search space is extended.
Diego Marcondes +2 more
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Remote Sensing, 2022 Tea is second only to water as the world’s most popular drink and it is consumed in various forms, such as black and green teas. A range of cultivars has therefore been developed in response to customer preferences.
Rei Sonobe, Yuhei Hirono
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Variable Selection in General Multinomial Logit Models [PDF]
, 2012 The use of the multinomial logit model is typically restricted to applications with few predictors, because in high-dimensional settings maximum likelihood estimates tend to deteriorate.
Pößnecker, Wolfgang +2 more
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Statistical Theory and Related FieldsVariable selection identifies the best subset of covariates when building the prediction model, among all possible subsets. In this paper, we propose a novel reinforced variable selection method, called ‘Actor-Critic-Predictor’. The actor takes an action
Yuan Le, Yang Bai, Fan Zhou
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Statistical Sources of Variable Selection Bias in Classification Tree Algorithms Based on the Gini Index [PDF]
, 2005 Evidence for variable selection bias in classification tree algorithms based on the Gini Index is reviewed from the literature and embedded into a broader explanatory scheme: Variable selection bias in classification tree algorithms based on the Gini ...
Strobl, Carolin
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Significance Analysis for Pairwise Variable Selection in Classification [PDF]
, 2014 The goal of this article is to select important variables that can distinguish one class of data from another. A marginal variable selection method ranks the marginal effects for classification of individual variables, and is a useful and efficient ...
Liu, Yufeng, Marron, J. S., Qiao, Xingye
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Variable Selection in Multivariable Regression Using SAS/IML
Journal of Statistical Software, 2002 This paper introduces a SAS/IML program to select among the multivariate model candidates based on a few well-known multivariate model selection criteria. Stepwise regression and all-possible-regression are considered.
Ali A. Al-Subaihi
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Latent class analysis variable selection [PDF]
, 2009 We propose a method for selecting variables in latent class analysis, which is the most common model-based clustering method for discrete data. The method assesses a variable's usefulness for clustering by comparing two models, given the clustering ...
A.E. Raftery +19 more
core +4 more sources