This paper deals with the task of "nding a set of prototypes from the training set. A reduced set is obtained which is used instead of the training set when nearest neighbour...
Cross validation can be used to detect when over tting starts during supervised training of a neural network; training is then stopped before convergence to avoid the overtting ...
The success of exploration-based training is likely to be strongly influenced by what activities the learner undertakes during training. This paper presents a study of the activiti...
Practice has shown that providing content to students alone is not sufficient for good learning results. In computer based training (CBT) and especially webbased training (WBT) en...
Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. I...
Abstract. People-centric sensor-based applications targeting mobile device users offer enormous potential. However, learning inference models in this setting is hampered by the lac...
Nicholas D. Lane, Hong Lu, Shane B. Eisenman, Andr...
Receiver Operating Characteristic (ROC) curves are a standard way to display the performance of a set of binary classifiers for all feasible ratios of the costs associated with fa...
In supervised learning, a training set consisting of labeled instances is used by a learning algorithm for generating a model (classifier) that is subsequently employed for decidi...
Authorship analysis of electronic texts assists digital forensics and anti-terror investigation. Author identification can be seen as a single-label multi-class text categorizatio...
In this paper we present a computational approach to developing effective training systems for virtual simulation environments. In particular, we focus on a Naval simulation syste...
Monica N. Nicolescu, Ryan E. Leigh, Adam Olendersk...