Background: The exploitation of information extraction (IE), a technology aiming to provide instances of structured representations from free-form text, has been rapidly growing w...
Tuangthong Wattarujeekrit, Parantu K. Shah, Nigel ...
The empirical error on a test set, the hold-out estimate, often is a more reliable estimate of generalization error than the observed error on the training set, the training estim...
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
Abstract. Approximations based on random Fourier features have recently emerged as an efficient and elegant methodology for designing large-scale kernel machines [4]. By expressing...
For many years now, there is a growing interest around ROC curve for characterizing machine learning performances. This is particularly due to the fact that in real-world problems ...