We describe in this paper the evolution of modular neural networks using hierarchical genetic algorithms for pattern recognition. Modular Neural Networks (MNN) have shown significant learning improvement over single Neural Networks (NN). For this reason, the use of MNN for pattern recognition is well justified. However, network topology design of MNN is at least an order of magnitude more diffi...

We built 3-D and 1-D look up tables (LUTs) to transform a user’s desired device-independent colors (CIELab) to the device-dependent color space (RGB). We considered experimental adaptive neighborhood and estimation methods for building the 3-D and 1-D LUTs. Methods of finding neighborhoods include: smallest enclosing neighborhood (SEN), smallest enclosing inclusive neighborhood (SENR), natural ...

The k nearest neighbor classification (k-NN) is a very simple and popular method for classification. However, it suffers from a major drawback, it assumes constant local class posterior probability. It is also highly dependent on and sensitive to the choice of the number of neighbors k. In addition, it severely lacks the desired probabilistic formulation. In this article, we propose a Bayesian ...

Purpose Exposure to various stressors, including psychological, metabolic, and immune, in the perinatal period induces long-lasting effects in physiological function and increase the risk of metabolic disorders in later life. In the present study, sexual maturation and sexual behavior were assessed in prenatally undernourished mature male rats. Methods All the pregnant rats were divided into ...

This paper analyzes if a multi-scale representation of geographical context based on statistical aggregates computed for individualized neighborhoods can lead to improved estimates of neighborhood effect. Our study group consists of individuals born in 1980 that have lived in Sweden since 1995 and we analyze the effect of neighborhood context at age 15 on educational outcome at age 30 controlli...

OBJECTIVE To assess the association between proximity to a needle exchange program (NEP) and experience of violence in an inner city neighborhood. METHODS A cross-sectional survey of residents of Harlem, New York City provided data for this study. We used geocoding to obtain the distance between respondents and the nearest NEP. Respondents reported violence they were aware of or had personall...

Robert Tibshirani Department of Statistics University of Toronto tibs@utstat .toronto.edu Nearest neighbor classification expects the class conditional probabilities to be locally constant, and suffers from bias in high dimensions We propose a locally adaptive form of nearest neighbor classification to try to finesse this curse of dimensionality. We use a local linear discriminant analysis to e...

The use of \global neural networks" (as the back propagation neural network) and \clustering neural networks" (as the radial basis function neural network) leads each other to diierent advantages and inconvenients. The combination of the desirable features ot those two neural ways of computation is achieved by the use of Modular Neural Networks (MNN). In addition, a considerable advantage can e...