Real-life applications, heavily relying on machine learning, such as dialog systems, demand for out-of-domain detection methods. Intent classification models should be equipped with a mechanism to distinguish seen intents from unseen ones so that the agent is capable of rejecting latter and avoiding undesired behavior. However, despite increasing attention paid task, best practices intent have ...

The classification of high dimensional data with kernel methods is considered in this article. Exploiting the emptiness property of high dimensional spaces, a kernel based on the Mahalanobis distance is proposed. The computation of the Mahalanobis distance requires the inversion of a covariance matrix. In high dimensional spaces, the estimated covariance matrix is ill-conditioned and its invers...

In previous work, semi-supervised Fuzzy c-means (ssFCM) was used as an automatic classification technique to classify the Nottingham Tenovus Breast Cancer (NTBC) dataset as no method to do this currently exists. However, the results were poor when compared with semi-manual classification. It is known that the NTBC data is highly non-normal and it was suspected that this affected the poor result...

This report describes a simulation model of sonar tracking, developed to explore the effect of networking sonars on tracking performance. The tracker is an extended Kalman filter with data association by nearest-neighbour in Mahalanobis distance. Data fusion algorithms also use Mahalanobis distance. Simulation outputs have been verified against analytical results where possible.