This paper extends previous work on skewing, an approach to problematic functions in decision tree induction. The previous algorithms were applicable only to functions of binary v...
Similarity metrics that are learned from labeled training
data can be advantageous in terms of performance
and/or efficiency. These learned metrics can then be used
in conjuncti...
We present new, general-purpose kernels for protein structure analysis, and describe how to apply them to structural motif discovery and function classification. Experiments show ...
—Techniques for detecting synthetic lethal mutations in double gene deletion experiments are emerging as powerful tool for analysing genes in parallel or overlapping pathways wit...
This paper concerns the use of real-valued functions for binary classification problems. Previous work in this area has concentrated on using as an error estimate the `resubstitut...