Results 211 to 220 of about 14,047 (249)
Some of the next articles are maybe not open access.
Discretisation in Lazy Learning Algorithms
Artificial Intelligence Review, 1997This paper adopts the idea of discretising continuous attributes (Fayyad and Irani 1993) and applies it to lazy learning algorithms (Aha 1990; Aha, Kibler and Albert 1991). This approach converts continuous attributes into nominal attributes at the outset.
openaire +1 more source
On unconventional discretisations
We present various discretisation techniques that mark a departure from the classical algorithms of numerical analysis, in the aim of preserving the physical behaviour of the solutions to the differential systems we are discretising, even for discretisation steps that are not very small.Grammaticos, Basil +2 more
openaire +1 more source
Discretisation Effects in Naive Bayesian Networks
2012Naive Bayesian networks are often used for classification problems that involve variables of a continuous nature. Upon capturing such variables, their value ranges are modelled as finite sets of discrete values. While the output probabilities and conclusions established from a Bayesian network are dependent of the actual discretisations used for its ...
Roel Bertens +2 more
openaire +2 more sources
2016
This paper looks at the distribution of selected adverbials used to discretise and quantify time in units of minutes, seconds and hours in reference language corpora of Polish and English. We carry out an exploratory analysis of the distributional patterns of such expressions and report three main findings.
Piotr Pęzik, Mikołaj Deckert
openaire +1 more source
This paper looks at the distribution of selected adverbials used to discretise and quantify time in units of minutes, seconds and hours in reference language corpora of Polish and English. We carry out an exploratory analysis of the distributional patterns of such expressions and report three main findings.
Piotr Pęzik, Mikołaj Deckert
openaire +1 more source
Discretisation for inference on normal mixture models
Statistics and Computing, 2003The problem of inference in Bayesian Normal mixture models is known to be difficult. In particular, direct Bayesian inference (via quadrature) suffers from a combinatorial explosion in having to consider every possible partition of n observations into k mixture components, resulting in a computation time which is O(kn).
openaire +2 more sources
On the discretisation of sparse linear systems
2014 European Control Conference (ECC), 2014Matheus Souza 0001 +3 more
openaire +2 more sources
Discretisation of the LES Models
2004This chapter deals with the discretisation of the LES models of the Navier-Stokes equations $$ \begin{gathered} w_t - \nabla \cdot ((2\nu + \nu _T ) \mathbb{D} (w)) + (w \cdot \nabla ) w \hfill \\ + \nabla r + \nabla \cdot \frac{{\delta ^2 }} {{2\gamma }}(A(\nabla w\nabla w^T )) = f in (0, T] \times \Omega , \hfill \\ \nabla \cdot w = 0 in [0, T ...
openaire +1 more source
The discretisation model of the SRM
1999The Switched Reluctance Motor (SRM) cross-section discretisation is critical concerning accuracy of its nonlinear magnetic field calculation based on the Finite Element Method (FEM). The generated mesh of the SRM is well adjusted to the physical and geometric characteristics of the problem.
Kovač, Nikša +2 more
openaire +1 more source
A compatible finite-element discretisation for the moist compressible Euler equations
Quarterly Journal of the Royal Meteorological Society, 2020Colin Cotter +2 more
exaly