Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
The large number of genes in microarray data makes feature selection techniques more crucial than ever. From various ranking-based filter procedures to classifier-based wrapper tec...
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
This paper describes a study performed in an industrial setting that attempts to build predictive models to identify parts of a Java system with a high probability of fault. The s...
It has been shown in prior work in management science, statistics and machine learning that using an ensemble of models often results in better performance than using a single ‘...