design a classifier. In this thesis, we present kernel methods for classification with irregularly sampled and contaminated … more discriminating power than those used by clinicians.Second, we consider one-class classification problem with …

components is selected to be used in a classification or a regression model to boost accuracy. A central issue in the PCA is how … ranking of principal components, the bootstrap and classification models. Unlike the classical approach, the algorithm we … necessarily be ordered. The ANOVA bootstrapped PCA classification we propose is novel as it automatically selects the number of …

variable length of the sequence. In this study we use logistic regression as the classification technique. A real sample of …