Implicit Model Selection Based on Variable Transformations in Estimation of Distribution
نویسندگان
چکیده
In this paper we address the problem of model selection in Estimation of Distribution Algorithms from a novel perspective. We perform an implicit model selection by transforming the variables and choosing a low dimensional model in the new variable space. We apply such paradigm in EDAs and we introduce a novel algorithm called I-FCA, which makes use of the independence model in the transformed space, yet being able to recover higher order interactions among the original variables. We evaluated the performance of the algorithm on well known benchmarks functions in a black-box context and compared with other popular EDAs.
منابع مشابه
MHD boundary layer flow and heat transfer of Newtonian nanofluids over a stretching sheet with variable velocity and temperature distribution
Laminar boundary layer flow and heat transfer of Newtonian nanofluid over a stretching sheet with the sheet velocity distribution of the form (Uw=CXβ) and the wall temperature distribution of the form (Tw= T∞+ axr) for the steady magnetohydrodynamic(MHD) is studied numerically. The governing momentum and energy equations are transformed to the local non-similarity equations using the appropriat...
متن کاملMHD Boundary Layer Flow and Heat Transfer of Newtonian Nanofluids over a Stretching Sheet with Variable Velocity and Temperature Distribution
Laminar boundary layer flow and heat transfer of Newtonian nanofluid over a stretching sheet with the sheet velocity distribution of the form (UW=cXβ) and the wall temperature distribution of the form (TW=T∞+aXr ) for the steady magnetohydrodynamic (MHD) is studied numerically. The governing momentum and energy equations are transformed to the local non-similarity equations using the appropriat...
متن کاملModel Selection for Mixture Models Using Perfect Sample
We have considered a perfect sample method for model selection of finite mixture models with either known (fixed) or unknown number of components which can be applied in the most general setting with assumptions on the relation between the rival models and the true distribution. It is, both, one or neither to be well-specified or mis-specified, they may be nested or non-nested. We consider mixt...
متن کاملBayesian Robust Variable and Transformation Selection: A Unified Approach
We consider the problem of simultaneous variable and transformation selection for linear regression. We propose a fully Bayesian solution to the problem, which allows us to average over all possible models including transformations of the response and predictors. We use the Box-Cox family of transformations to transform the response and each predictor. To deal with the change of scale induced b...
متن کاملOn Concomitants of Order Statistics from Farlie-Gumbel-Morgenstern Bivariate Lomax Distribution and its Application in Estimation
‎In this paper‎, ‎we have dealt with the distribution theory of concomitants of order statistics arising from Farlie-Gumbel-Morgenstern bivariate Lomax distribution‎. ‎We have discussed the estimation of the parameters associated with the distribution of the variable Y of primary interest‎, ‎based on the ranked set sample defined by ordering the marginal observations...
متن کامل