since the change of land use accrued in the iran, especially in northern iran, this research aims tocompare the spatial variability of soil properties in three adjacent land uses including cultivated by wheat lands, grazing lands and forest lands covered by juniperus sp,  fagus orientalis, quercus castanifolia, and acer velotinum species in kiasar region, mazandaran province, northern iran. som...

MOTIVATION Numerous competing algorithms for prediction in high-dimensional settings have been developed in the statistical and machine-learning literature. Learning algorithms and the prediction models they generate are typically evaluated on the basis of cross-validation error estimates in a few exemplary datasets. However, in most applications, the ultimate goal of prediction modeling is to ...

Model selection is one of the key issues both in recent research and application of kernel methods. Cross-validation is a commonly employed and widely accepted model selection criterion. However, it requires multiple times of training the algorithm under consideration, which is computationally intensive. In this paper, we present a novel strategy for approximating the cross-validation based on ...

Number of latents The same number of factors will be extracted for PLS responses as for PLS factors. The researcher must specify how many latents to extract (in SPSS the default is 5). There is no one criterion for deciding how many latents to employ. Common alternatives are: 1. Cross-validating the model with increasing numbers of factors, then choosing the number with minimum prediction error...

We assessed the criterion related validity of 1/2 mile run/walk (1/2MRW) test for estimating VO2peak in children aged 6-17 years. The criterion related validity of the Fernhall's equation in a sub-group of children aged 10-17 years was also examined. A total of 86 children completed a maximal graded treadmill test and the 1/2MRW test. The cohort was randomly divided into either validation (n=47...

First, we analyze the variance of Cross Validation (CV)-based estimators used for estimating performance classification rules. Second, propose a novel estimator to estimate this using Influence Function (IF) approach that had been previously very successfully bootstrap-based estimators. The motivation research is that, as best our knowledge, literature lacks rigorous method CV-based What availa...

Tuning parameters in supervised learning problems are often estimated by cross-validation. The minimum value of the cross-validation error can be biased downward as an estimate of the test error at that same value of the tuning parameter. We propose a simple method for the estimation of this bias that uses information from the crossvalidation process. As a result, it requires essentially no add...

In the sequential approach to three-dimensional reconstruction, adding prior knowledge about camera pose improves reconstruction accuracy. We add a smoothing penalty on the camera trajectory. The smoothing parameter, usually fixed by trial and error, is automatically estimated using Cross-Validation. This technique is extremely expensive in its basic form. We derive Gauss-Newton Cross-Validatio...