The strength of association between a pair of data vectors is represented by a nonnegative real number, called matching weight. For dimensionality reduction, we consider a linear transformation of data vectors, and define a matching error as the weighted sum of squared distances between transformed vectors with respect to the matching weights. Given data vectors and matching weights, the optima...

Given the relatively small number of microarrays typically used in gene-expression-based classification, all of the data must be used to train a classifier and therefore the same training data is used for error estimation. The key issue regarding the quality of an error estimator in the context of small samples is its accuracy, and this is most directly analyzed via the deviation distribution o...

MOTIVATION Supervised machine learning is commonly applied in genomic research to construct a classifier from the training data that is generalizable to predict independent testing data. When test datasets are not available, cross-validation is commonly used to estimate the error rate. Many machine learning methods are available, and it is well known that no universally best method exists in ge...

Choosing optimal hyperparameters for support vector machines is an important step in SVM design. This is usually done by minimizing either an estimate of generalization error or some other related performance measures. In this paper, we empirically study the usefulness of several simple performance measures that are very inexpensive to compute. The results point out which of these performance m...

Introduction: In humans skin blood flow (SBF) plays a major role in body heat loss. Therefore the accuracy of models of human thermoregulation depends for a great deal on their ability to predict skin blood flow. Most SBF-models use body temperatures directly for calculation of skin perfusion. However, humans do not sense temperature directly, yet the information is coded into neuron fire rates...

This paper describes some methodological issues to be considered when designing systems for automatic detection of voice pathology, in order to allow comparisons with previous or future experiments. The proposed methodology is built around Kay Elemetrics voice disorders database, which is the only one commercially available. Discussion about key points on this database is included. Any experime...

When modelling a large area, models that can take into a count the variation from the general mean in small sub-areas could perform better in prediction than a general model fitted to entire dataset. One method for adjusting the large-area models for such variation is kriging, in which the predictions are corrected with the aid of neighbouring observations. A variogram represents the spatial co...

This paper provides a systematic procedure for computing the regional average of climate data in a subregion of the earth surface using the covariance function written in terms of empirical orthogonal functions (EOFs). The method is optimal in the sense of minimum mean square error (mse) and gives an mse estimate of the averaging results. The random measurement error is also included in the tot...