leave-one-out approach
Predictors of Treatment Adherence in Adolescents with Inflammatory Bowel Disease: The Role of Age, Body Satisfaction and Prospective Memory in Medication and Diet Behavior
... ‘leave-one-out’ approach [42], as SNP-dropping) assumes both that the sample size is big enough that the haplotype frequencies are representative of the whole population, and that the observed ...
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Spatial Analysis Approach in Revealing the Global Sinks of Atmosphere Carbon Dioxide through “Leave One Out” Method
... [27]. One of the first to investigate the concept of spatial autocorrelation was Moran (1947, 1948), and the second one was Geary (1954) who formulated another measure ...
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KCCA-based technique for profile face identification
... a leave one out- like protocol ...conventional leave one out (LOO) procedure [37], with a dataset of size n in hand, at each validation step, n − 1 individuals are used to train ...
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Determining optimal neighborhood size for ecological studies using leave-one-out cross validation
... that one can determine optimal neighborhood for ecological studies in health using the leave-one-out cross validation that measures contextual information within a circular area centered on ...
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Automatic kernel regression modelling using combined leave one out test score and regularised orthogonal least squares
... Because parameter regularisation and robust model structure selection are effective and complementary approaches for robust modelling, it is highly desirable to develop algorithms by combining parameter regularisation ...
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Comparison of cross-validation and bootstrap aggregating for building a seasonal streamflow forecast model
... first approach selects a single “best guess” model, which is tested by leave-one-out ...second approach implements the idea of bootstrap aggregating, where bootstrap replicates are ...
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Bayesian Leave-One-Out Cross-Validation Approximations for Gaussian Latent Variable Models
... Above we saw that the methods other than LA-LOO and EP-LOO had more difficulties with most of the data sets and especially with data sets with a large number of covariates. Figures 1–4 illustrate how the flexibility of ...
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Semiparametric penalty function method in partially linear model selection
... semiparametric leave– more–out cross–validation selection procedure for the choice of both the parametric and nonparametric regressors in a nonlinear time series regression ...the ...
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Sparse kernel density construction using orthogonal forward regression with leave one out test score and local regularization
... Abstract—This paper presents an efficient construction algo- rithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability. ...
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Can I Leave This One Out? The Effect of Dropping an Item From the SUS
... promising approach would be to systematically examine the effect of dropping a problematic item—an approach that can be performed using historical SUS data without the need to collect new ...
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Hardy-Type Inequalities via Auxiliary Sequences
... shall leave the explanation of Knopp’s approach in detail in Section 2 by pointing out here that it can be applied to prove other types of inequalities similar to that of ...
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Sparse kernel density construction using orthogonal forward regression with leave one out test score and local regularization
... Abstract— The paper presents an efficient construction algo- rithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability. ...
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Fast kernel classifier construction using orthogonal forward selection to minimise leave one out misclassification rate
... This paper considers the construction of parsimonious two-class linear-in-the- parameters kernel classifiers using LOO cross validation. The proposed method extends the OFS procedure for regression in [12,13] to the ...
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Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction
... published approach to use marker or haplotype information fits breeding values as random effects based on covariances defined by a “genomic relationship matrix” computed from genotypes ...
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Fast kernel classifier construction using orthogonal forward selection to minimise leave one out misclassification rate
... Overview of Existing Methods o Nonlinear optimisation approach: Optimise all parameters kernel centre vectors, variances or covariance matrices, and weights P Very “sparse” small size P [r] ...
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Leave One Out Phrase Model Training for Large Scale Deployment
... This work concentrates on practical issues with large and noisy training data. Our main goal is to ap- ply phrase training to reduce phrase table size with- out sacrificing quality. We do this by dumping n- best ...
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Construction of RBF classifiers with tunable units using orthogonal forward selection based on leave one out misclassification rate
... Motivations o How good a RBF classifier method: P Generalisation performance P Sparsity level or classifier’s size P Efficiency of classifier construction process o Combine best of both [r] ...
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Sentiment Analysis of Twitter Data using Naïve Bayes with Unigram Approach
... K-fold cross validation acts as an improvement of the hideout method. The dataset is repeated k times and divided into k subsets in k-fold cross validation method. In each instance only one of the k sets are used ...
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QSAR STUDY OF INDANE-URIEDO-THIOISOBUTYRIC ACIDS AS A PPARα AGONISTS
... by leave one out (LOO) cross validation method and test and training set method, which furnished squared cross correlation co-efficient (r 2 or q 2 ), standard error of squared ...
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In One Ear, Out The Other
... Later summit councils such as Cardiff (June 1998) and Cologne (March 1999) shaped the form and structure of such necessary instruments. During these summits, the Heads of State and Government of the Member States ...
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