Stacking is a widely used technique for combining classifiers and improving prediction accuracy. Early research in Stacking showed that selecting the right classifiers, their par...
We combine two complementary ideas for learning supertaggers from highly ambiguous lexicons: grammar-informed tag transitions and models minimized via integer programming. Each st...
Multi-classifier approach is a widespread strategy used in many difficult classification problems. Traditionally, in a multi-classifier approach, a classification decision based o...
Giuseppe Pirlo, Claudia Adamita Trullo, Donato Imp...
Emotion words have been well used as the most obvious choice as feature in the task of textual emotion recognition and automatic emotion lexicon construction. In this work, we exp...
: A multiple test procedure for assessing multivariate normality (MVN) that combines a finite set of affine invariant test statistics for MVN is proposed. This combination is base...