Buscar recursos académicos

The use of some multiple-sequence alignments in phylogenetic analysis, particularly those that are not very well conserved, requires the elimination of poorly aligned positions and divergent regions, since they may not b...

We present a study of using fuzzy-based parameters for solving public bus routing problem where demand is uncertain. The fuzzy-based parameters are designed to provide data required by the route selection procedure. The ...

The metric spaces model formalizes the similarity search concept in nontraditional databases. The goal is to build an index designed to save distance computations when answering similarity queries later. A large class of...

The performance of two selection mechanisms used in the most popular variant of differential evolution, known as DE/rand/1/bin, are compared in the solution of constrained numerical optimization problems. Four performanc...

Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the dif...

Introduction * Information and Likelihood Theory: A Basis for Model Selection and Inference * Basic Use of the Information-Theoretic Approach * Formal Inference From More Than One Model: Multi-Model Inference (MMI) * Mon...

SUMMARY We propose a new method for estimation in linear models. The ‘lasso’ minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of t...

Summary We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often outperforms the lasso, while enjoying a similar sparsity of r...

Sample selection bias as a specification error This paper discusses the bias that results from using non-randomly selected samples to estimate behavioral relationships as an ordinary specification error or «omitted vari...

Variable selection is fundamental to high-dimensional statistical modeling, including nonparametric regression. Many approaches in use are stepwise selection procedures, which can be computationally expensive and ignore ...

Materias / palabras clave: Classifier (UML); Gene; Computer science; Feature selection; Redundancy (engineering); Gene selection; Support vector machine; Computational biology; sort; Artificial intelligence; Pattern recognition (psychology); Data ...

Materias / palabras clave: Phylogenetic tree; Selection (genetic algorithm); Computational biology; Evolutionary biology; Model selection; Biology; Phylogenetics; Computer science; Genetics; Artificial intelligence; Gene

Materias / palabras clave: Feature selection; Artificial intelligence; Selection (genetic algorithm); Computer science; Feature (linguistics); Pattern recognition (psychology); Machine learning; Linguistics; Philosophy

A data warehouse efficiently processes a given set of queries by utilizing the multiple materialized views. Owing to the constraint on space and maintenance cost, the materialization of all views is unfeasible. One of th...

Similarity search is a fundamental operation for applications that deal with unstructured data sources. In this paper we propose a new pivot-based method for similarity search, called Sparse Spatial Selection (SSS). The...

Nowadays,it's well-known that Small and Medium Enterprises (SMEs) generate important contributions to the software industry. Their particular characteristics constitute a challenge to decision makers when selecting techn...

This study aims to evaluate the criteria and procedures for the selection of antidiabetic and antihypertensive drugs purchased by the public health network of the cities in the Ourinhos Micro-region, Sao Paulo, Brazil....

Part 1 Genetic constitution of a population: Hardy-Weinberg equilibrium. Part 2 Changes in gene frequency: migration mutation. Part 3 Small populations - changes in gene frequency under simplified conditions. Part 4 Smal...

The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we ...

The model selection literature has been generally poor at reflecting the deep foundations of the Akaike information criterion (AIC) and at making appropriate comparisons to the Bayesian information criterion (BIC). There...

The following paper presents current thinking and research on fit indices for structural equation modelling. The paper presents a selection of fit indices that are widely regarded as the most informative indices availabl...

The ability to afford decision makers with both accurate and timely consolidated information as well as rapid query response times is the fundamental requirement for the success of a Data Warehouse. To provide fast acces...

The R package mice imputes incomplete multivariate data by chained equations. The software mice 1.0 appeared in the year 2000 as an S-PLUS library, and in 2001 as an R package. mice 1.0 introduced predictor selection, pa...

One of the problems which has plagued those attempting to predict the behavior of capital markets is the absence of a body of positive microeconomic theory dealing with conditions of risk. Although many useful insights c...