Identifying areas prone to flooding is a key step in flood risk management. The purpose of this study develop and present novel susceptibility model based on Bayesian Additive Regression Tree (BART) methodology. predictive performance the new assessed via comparison with Naïve Bayes (NB) Random Forest (RF) methods that were previously published literature. All models tested real case Kan waters...

Abstract Regression analysis is a statistical procedure that fits mathematical function to set of data in order capture the relationship between dependent and independent variables. In tree regression, structures are constructed by repeated splits input space into two subsets, creating if-then-else rules. Such models popular literature due their ability be computed quickly simple interpretation...

A regression graph to enumerate and evaluate all possible subset regression models is introduced. The graph is a generalization of a regression tree. All the spanning trees of the graph are minimum spanning trees and provide an optimal computational procedure for generating all possible submodels. Each minimum spanning tree has a different structure and characteristics. An adaptation of a branc...

The main aim of this paper is to develop a suitable regression analysis model for describing the relationship between the index efficiency and the parameters of the Rival Penalized Competitive Learning Binary Tree (RPCLb-tree). RPCL-b-tree is a hierarchical indexing structure built with a hierarchical RPCL clustering implementation, which transforms the feature space into a sequence of nested c...

Amethod of generalized regression that blends tree-structured nonparametric regression and adaptive recursive partitioning with maximum likelihood estimation is studied. The function estimate is a piecewise polynomial, with the pieces determined by the terminal nodes of a binary decision tree. The decision tree is constructed by recursively partitioning the data according to the signs of the re...

A method of generalized regression that blends tree-structured nonparametric regression and adaptive recursive partitioning with maximum likelihood estimation is studied. The function estimate is a piecewise polynomial, with the pieces determined by the terminal nodes of a binary decision tree. The decision tree is constructed by recursively partitioning the data according to the signs of the r...

conclusions: absence of the c allele was significantly associated with failure of response. the presence of c allele was associated with a favorable outcome. afp is a strong baseline predictor of hcv treatment response. a decision tree model is useful for predicting the probability of response to therapy. patients and methods: the study included 263 chronic hcv egyptian patients receiving peg-i...

abstract: converting point data to continuous one is the first step in order to use them in scorpan flowchart. for this purpose, different geostatistic methods are available which at present research regression kriging with local variogram was applied. for mapping apparent electrical conductivity at the area covering 72000ha located in ardakan region, 700 readings in horizontal and vertical mod...