Results 51 to 60 of about 8,137,182 (304)
American Journal of Theoretical and Applied StatisticsEffective model evaluation is crucial for robust machine learning, and cross-validation techniques play a significant role. This study compares Repeated k-folds Cross Validation, k-folds Cross Validation, and Leave-One-Out Cross Validation (LOOCV) on ...
Victor Lumumba +4 more
semanticscholar +1 more source
Efficient algorithms for decision tree cross-validation
, 2001 Cross-validation is a useful and generally applicable technique often employed in machine learning, including decision tree induction. An important disadvantage of straightforward implementation of the technique is its computational overhead.
Blockeel, Hendrik, Struyf, Jan
core +4 more sources
Ordered quantile normalization: a semiparametric transformation built for the cross-validation era
Journal of Applied Statistics, 2019 Normalization transformations have recently experienced a resurgence in popularity in the era of machine learning, particularly in data preprocessing. However, the classical methods that can be adapted to cross-validation are not always effective.
Ryan A. Peterson, J. Cavanaugh
semanticscholar +1 more source
Remote Sensing, 2015 Much remote sensing (RS) research focuses on fusing, i.e., combining, multi-resolution/multi-sensor imagery for land use/land cover (LULC) classification. In relation to this topic, Sun and Schulz [1] recently found that a combination of visible-to-near
Brian A. Johnson
doaj +1 more source
Multiplicative local linear hazard estimation and best one-sided cross-validation [PDF]
, 2017 This paper develops detailed mathematical statistical theory of a new class of cross-validation techniques of local linear kernel hazards and their multiplicative bias corrections.
Gámiz Pérez, M. L. +2 more
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Sickle Cell Disease Is an Inherent Risk for Asthma in a Sibling Comparison Study
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Sickle cell disease (SCD) and asthma share a complex relationship. Although estimates vary, asthma prevalence in children with SCD is believed to be comparable to or higher than the general population. Determining whether SCD confers an increased risk for asthma remains challenging due to overlapping symptoms and the ...
Suhei C. Zuleta De Bernardis +9 more
wiley +1 more source
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Cross-validation (CV) is the most widely adopted approach for selecting the optimal model. However, the computation of CV has high complexity due to multiple times of learner training, making it disabled for large scale model selection. In this paper, we present an approximate approach to CV based on the theoretical notion of Bouligand influence ...
Yong Liu +4 more
openaire +1 more source
Fast Cross-Validation via Sequential Testing [PDF]
, 2015 With the increasing size of today's data sets, finding the right parameter configuration in model selection via cross-validation can be an extremely time-consuming task.
Braun, Mikio +2 more
core
Consistency of cross validation for comparing regression procedures
, 2008 Theoretical developments on cross validation (CV) have mainly focused on selecting one among a list of finite-dimensional models (e.g., subset or order selection in linear regression) or selecting a smoothing parameter (e.g., bandwidth for kernel ...
Yang, Yuhong
core +1 more source
IEEE Access, 2020 Human Activity Recognition (HAR) has been attracting significant research attention because of the increasing availability of environmental and wearable sensors for collecting HAR data.
Davoud Gholamiangonabadi +2 more
semanticscholar +1 more source