Confidence-weighted (CW) learning [6], an online learning method for linear classifiers, maintains a Gaussian distributions over weight vectors, with a covariance matrix that repr...
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...
Many important application areas of text classifiers demand high precision and it is common to compare prospective solutions to the performance of Naive Bayes. This baseline is us...
To understand the subjective documents, for example, public comments on the government’s proposed regulation, opinion identification and classification is required. Rather than ...
Namhee Kwon, Liang Zhou, Eduard H. Hovy, Stuart W....