Stratified sampling is a sampling method that takes into account the existence of disjoint groups within a population and produces samples where the proportion of these groups is maintained. In single-label classification tasks, groups are differentiated based on the value of the target variable. In multi-label learning tasks, however, where there are multiple target variables, it is not clear ...

We analyze and compare the efficiency and accuracy of two simulation methods for homogeneous random fields with multiscale resolution. We consider in particular the Fourier-wavelet method and three variants of the Randomization method: (A) without any stratified sampling of wavenumber space, (B) with stratified sampling of wavenumbers with equal energy subdivision, (C) with stratified sampling ...

SampleBoost is an intelligent multi-class boosting algorithm that employs an error parameter combined with stratified sampling during training iterations to accommodate multi-class data sets and avoid problems associated with traditional boosting methods. In this paper we investigate the choice of the error parameter along with the preferred sampling sizes for our method. Experimental results s...

For high dimensional data a large portion of features are often not informative of the class of the objects. Random forest algorithms tend to use a simple random sampling of features in building their decision trees and consequently select many subspaces that contain few, if any, informative features. In this paper we propose a stratified sampling method to select the feature subspaces for rand...

This study uses Monte Carlo simulation to examine the impact of nine sampling strategies on the finite sample performance of the maximum likelihood logit estimator. Empirical researchers face a tradeoff between the lower resource costs associated with smaller samples and the increased confidence in the results gained from larger samples. Choice of sampling strategy is one tool researchers can u...

Let C be an isolated plane curve singularity, and (C, l) be a decorated curve. In this article we compare the equisingular deformations of C and the sandwiched singularity X(C, l). We will prove that for l ≫ 0 the functor of equisingular deformations of C and (C, l) are equivalent. From this we deduce a proof of a formula for the dimension of the equisingular stratum. Furthermore we will show h...

In this study, we propose a two stage randomized response model. Improved unbiased estimators of the mean number of persons possessing a rare sensitive attribute under two different situations are proposed. The proposed estimators are evaluated using a relative efficiency comparison. It is shown that our estimators are efficient as compared to existing estimators when the parameter of rare unre...

In this research, the covariance estimates were used to estimate population mean in stratified random sampling and combined regression estimates. compared by employing robust variance-covariance matrices with traditional when estimating parameter, through two efficiency criteria (RE) squared error (MSE). We found that significantly improved quality of reducing effect outliers using (MCD, MVE) p...