Given a collection of sentences, S, the task is to label each sentence as either speculative or nonspeculative (spec or nspec henceforth).
the training and classification models we have presented require the setting of two parameters: the smoothing parameter α and the number of features per sample m. Analysis of the effect of varying α on feature ranking reveals that when α = 0, low frequency terms with spurious class correlation dominate and as α increases, high frequency terms become increasingly dominant, eventually smoothing away genuine low-to-mid frequency correlations.