Building a model using machine learning that can classify the sentiment of natural language text often requires an extensive set of labeled training data from the same domain as t...
We present Confidence-based Feature Acquisition (CFA), a novel supervised learning method for acquiring missing feature values when there is missing data at both training and test...
Marie desJardins, James MacGlashan, Kiri L. Wagsta...
We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...
Finding effective methods for developing an ensemble of models has been an active research area of large-scale data mining in recent years. Models learned from data are often subj...
Background: We present a novel strategy for classification of DNA molecules using measurements from an alpha-Hemolysin channel detector. The proposed approach provides excellent c...
Raja Tanveer Iqbal, Matthew Landry, Stephen Winter...