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865
HyperRectangular and kNearestNeighbor Models in Stochastic Discrimination
"... Abstract — The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in several application domains, a number of difficulties related to its practical implementation still exist. Thi ..."
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to maintain the projectability condition, the other constructs hyperrectangular regions by randomly selecting subintervals in each dimension. Analysis of these implementations shows that for highdimensional data, parallel model generation with the nearest neighbor approach is a favorable alternative
EQUIPARTITIONING OF HIGHERDIMENSIONAL HYPERRECTANGULAR GRID GRAPHS
"... A ddimensional grid graph G is the graph on a finite subset in the integer lattice Z d in which a vertex x = (x1, x2, · · · , xn) is joined to another vertex y = (y1, y2, · · · , yn) if for some i we have xi − yi  = 1 and xj = yj for all j � = i. G is hyperrectangular if its set of verti ..."
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Cited by 1 (0 self)
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A ddimensional grid graph G is the graph on a finite subset in the integer lattice Z d in which a vertex x = (x1, x2, · · · , xn) is joined to another vertex y = (y1, y2, · · · , yn) if for some i we have xi − yi  = 1 and xj = yj for all j � = i. G is hyperrectangular if its set
Conference on Data Mining  DMIN'06  57 HyperRectangular and kNearestNeighbor Models in Stochastic Discrimination
"... Abstract — The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in several application domains, a number of difficulties related to its practical implementation still exist. Thi ..."
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to maintain the projectability condition, the other constructs hyperrectangular regions by randomly selecting subintervals in each dimension. Analysis of these implementations shows that for highdimensional data, parallel model generation with the nearest neighbor approach is a favorable alternative
An Adaptive Algorithm for the Approximate Calculation of Multiple Integrals
, 1991
"... An adaptive algorithm for numerical integration over hyperrectangular regions is described. The algorithm uses a globally adaptive subdivision strategy. Several precautions are introduced in the error estimation in order to improve the reliability. In each dimension more than one integration rule ..."
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Cited by 66 (7 self)
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An adaptive algorithm for numerical integration over hyperrectangular regions is described. The algorithm uses a globally adaptive subdivision strategy. Several precautions are introduced in the error estimation in order to improve the reliability. In each dimension more than one integration
PAMIHR. A Parallel FORTRAN Program for Multidimensional Quadrature on Distributed Memory Architectures
"... Abstract. PAMIHR: a parallel adaptive routine for the approximate computation of a multidimensional integral over a hyperrectangular region is described. The software is designed to efficiently run on a MIMD distributed memory environment, and it's based on the widely diffused communication sy ..."
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Abstract. PAMIHR: a parallel adaptive routine for the approximate computation of a multidimensional integral over a hyperrectangular region is described. The software is designed to efficiently run on a MIMD distributed memory environment, and it's based on the widely diffused communication
A Hybrid SymbolicNumeric Method for Multiple Integration Based on TensorProduct Series Approximations
 In: Proceedings of CoNLL2000 and LLL2000
, 2004
"... This work presents a new hybrid symbolicnumeric method for fast and accurate evaluation of multiple integrals, e#ective both in high dimensions and with high accuracy. In two dimensions, the thesis presents an adaptive twophase algorithm for double integration of continuous functions over general ..."
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Cited by 2 (0 self)
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of integrands with special structure over hyperrectangular regions.
Adaptive Multivariate Integration using MPI
, 1997
"... We describe a coarse grain parallel algorithm for multivariate adaptive integration using MPI. The algorithm is asynchronous in nature and allows for load balancing. Timing results show good speedups obtained on a network of workstations for a class of integrals from Bayesian statistics. 1 Introduc ..."
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is supplied a specification of the vector integrand function ~ f(~x) and the integration region D, an absolute and a relative tolerance, " a and " r , respectively, and a limit on the number of integrand evaluations to be performed during the course of the computations. D is a hyperrectangular
Methods for the Computation of Multivariate tProbabilities
 Computing Sciences and Statistics
, 2000
"... This paper compares methods for the numerical computation of multivariate tprobabilities for hyperrectangular integration regions. Methods based on acceptancerejection, sphericalradial transformations and separationofvariables transformations are considered. Tests using randomly chosen problems ..."
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Cited by 84 (11 self)
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This paper compares methods for the numerical computation of multivariate tprobabilities for hyperrectangular integration regions. Methods based on acceptancerejection, sphericalradial transformations and separationofvariables transformations are considered. Tests using randomly chosen
Mining Oblique Data with XCS
 PROCEEDINGS OF THE THIRD INTERNATIONAL WORKSHOP (IWLCS2000), LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
, 2000
"... The classifier system XCS was investigated for data mining applications where the dataset discrimination surface (DS) is generally oblique to the attribute axes. Despite the classifiers' hyperrectangular predicates, XCS reached 100% performance on synthetic problems with diagonal DS's a ..."
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Cited by 50 (2 self)
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The classifier system XCS was investigated for data mining applications where the dataset discrimination surface (DS) is generally oblique to the attribute axes. Despite the classifiers' hyperrectangular predicates, XCS reached 100% performance on synthetic problems with diagonal DS
#include <nag.h>
"... nag_multid_quad_monte_carlo_1 (d01xbc) evaluates an approximation to the integral of a function over a hyperrectangular region, using a Monte Carlo method. An approximate relative error estimate is also returned. This function is suitable for low accuracy work. ..."
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nag_multid_quad_monte_carlo_1 (d01xbc) evaluates an approximation to the integral of a function over a hyperrectangular region, using a Monte Carlo method. An approximate relative error estimate is also returned. This function is suitable for low accuracy work.
Results 1  10
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865