Stochastic Learning-Based Estimation Methods for Pattern Recognition and Its Application to Topic Detection and Tracking

2008

Masteroppgave i informasjons- og kommunikasjonsteknologi 2008 – Universitetet i Agder, Grimstad Every Pattern Recognition (PR) problem involves a training and a testing phase. In the training phase, the system is presented with samples, using which the distribution (also called the classconditional distribution), of the features, is estimated. Traditional PR systems assume that the class-conditional distributions are stationary, and thus that they do not change with time. Recently Oommen and his co-authors have presented a strategy by which the parameters of a binomial/- multinomial distribution can be estimated when the distribution is non-stationary. In this thesis, we propose a selection…