Most of machine learning approaches have stemmed from the application of minimizing the mean squared distance principle, based on the computationally efficient quadratic optimization methods. However, when faced with high-dimensional and noisy data, the quadratic error functionals demonstrated many weaknesses including high sensitivity to contaminating factors and dimensionality curse. Therefor...

There is little research data available on the digestible Lys requirement of broilers from 2 to 4 wk of age. Two experiments were conducted to determine the digestible Lys requirements of male and female Ross x Ross TP16 broilers from 14 to 28 d. Two diets (dilution and summit) consisting of corn, soybean meal, poultry by-product meal, and peanut meal were formulated to be adequate in all other...

BACKGROUND Popular predictive models for estimating morbidity probability after heart surgery are compared critically in a unitary framework. The study is divided into two parts. In the first part modelling techniques and intrinsic strengths and weaknesses of different approaches were discussed from a theoretical point of view. In this second part the performances of the same models are evaluat...

Quadratic penalties can be used to incorporate external knowledge about the association structure among regressors. Unfortunately, they do not enforce single estimated regression coefficients to equal zero. In this paper we propose a new approach to combine quadratic penalization and variable selection within the framework of generalized linear models. The new method is called Forward Boosting ...

Many real life situations can be described using twice continuously differentiable functions over convex sets with interior points. Such functions have an interesting separation property: At every interior point of the set they separate particular classes of quadratic convex functions from classes of quadratic concave functions. Using this property we introduce new characterizations of the deri...

Discriminant analysis of chemistry and hematology laboratory test results was used to classify patients with and without myocardial infarction in a coronary care unit. We studied 64 patients with myocardial infarction and 70 patients without infarction, using logistic regression, linear and quadratic discriminant analyses on untransformed and logarithmically transformed data. Serum aspartate am...

We consider a linear regression problem in a high dimensional setting where the number of covariates p can be much larger than the sample size n. In such a situation, one often assumes sparsity of the regression vector, i.e., the regression vector contains many zero components. We propose a Lasso-type estimator β̂ (where ‘Quad’ stands for quadratic) which is based on two penalty terms. The first...

Supervised learning of classifiers often resorts to the minimization of a quadratic error, even if this criterion is more especially matched to nonlinear regression problems. It is shown that the mapping built by a quadratic error minimization (QEM) tends to output the Bayesian discriminating rules even with nonuniform losses, provided the desired responses are chosen accordingly. This property...