Document classification is a key task for many text mining applications. However, traditional text classification requires labeled data to construct reliable and accurate classifie...
Protein function prediction is an active area of research in bioinformatics. And yet, transfer of annotation on the basis of sequence or structural similarity remains widely used ...
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
In this paper we generalize the LARS feature selection method to the linear SVM model, derive an efficient algorithm for it, and empirically demonstrate its usefulness as a featur...
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...