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...
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Multiclass cancer classification on microarray data has provided the feasibility of cancer diagnosis across all of the common malignancies in parallel. Using multiclass cancer feat...
Background: In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of...
Fan Shi, Christopher Leckie, Geoff MacIntyre, Izha...
The large number of genes and the relatively small number of samples are typical characteristics for microarray data. These characteristics pose challenges for both sample classif...