In the present paper, we propose and analyze a novel method for estimating a univariate regression function of bounded variation. The underpinning idea is to combine two classical tools in nonparametric statistics, namely isotonic regression and the estimation of additive models. A geometrical interpretation enables us to link this iterative method with Von Neumann’s algorithm. Moreover, making...

recognition equal units and segregation them and upshot planning per units most basic method for management forest units. aim this study presentation and comparison classification and regression tree (cart) and random forest (rf) algorithm for forest type mapping using aster satellite data in district one didactic and research forest's darabkola. in start using inventory network 500* 350 m...

Identifying regions of DNA that contribute to disease becomes more difficult as the diseases become more complex. Traits such as blood pressure or heart disease have complex etiologies involving multiple genes or gene by environment interactions. In these cases, many current models are too simple to detect the effects of genes. Recently, Shannon et al. proposed the use of recursive partitioning...

the effect of boundary conditions on the solution of the inverse problem of identifying the geometry and location of a cavity inside an elastic solid body using displacement measurements obtained from a tension test is investigated. the boundary elements method (bem) coupled with the genetic algorithm (ga) and the conjugate gradient method (cgm) are implemented in this identification problem. a...

In this paper, we discuss how to approximate the conditional expectation of a random variable Y given a random variable X, i.e. E(Y|X). We propose and compare two different non parametric methodologies to approximate E(Y|X). The first approach (namely the OLP method) is based on a suitable approximation of the σ-algebra generated by X. A second procedure is based on the well known kernel non-pa...

a simple and rapid method for the determination of 137ba isotope abundances in water samples by inductively coupled plasma-optical emission spectrometry (icp-oes) coupled with least-squares support vector machine regression (ls-svm) is reported. by evaluation of emission lines of barium, it was found that the emission line at 493.408 nm provides the best results for the determination of 137ba a...

Missing values in datasets should be extracted from the datasets or should be estimated before they are used for classification, association rules or clustering in the preprocessing stage of data mining. In this study, we utilize a fuzzy c-means clustering hybrid approach that combines support vector regression and a genetic algorithm. In this method, the fuzzy clustering parameters, cluster si...