—High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray ana...
Chan-Hoon Park, Soo-Jin Kim, Sun Kim, Dong-Yeon Ch...
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
We approached the problem of classifying papers for the TREC 2004 Genomics Track triage task as a four step process: feature generation, feature selection, classifier training, an...
Aaron M. Cohen, Ravi Teja Bhupatiraju, William R. ...
The nearest shrunken centroid classifier uses shrunken centroids as prototypes for each class and test samples are classified to belong to the class whose shrunken centroid is nea...
Many real-world domains present the problem of imbalanced data sets, where examples of one classes significantly outnumber examples of other classes. This makes learning difficu...