May 24, 2005 · We present a systematic approach to evaluate the performance of different feature sets based on recursive feature elimination, RFE. Based on a ...

This helps us to identify descriptive features, to learn about the structure of the problem, and to design systems that are faster and easier to understand. We ...

High weighted features are more likely to apply to positive samples (NEWGENE), low weighted features to negative samples. Names in bold indicate binary ...

We present a systematic approach to evaluate the performance of different feature sets based on recursive feature elimination, RFE. Based on a systematic ...

Abstract In task 1A of the BioCreAtIvE evaluation, systems had to be devised that recognize words and phrases forming gene or protein names in natural ...

We present a systematic approach to evaluate the performance of different feature sets based on recursive feature elimination, RFE. Based on a systematic ...

We compared the performance of 41 analysis models based on 14 software packages and different data sets, including high-quality data and low-quality data from ...

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(2005), 'Systematic feature evaluation for gene name recognition', BMC Bioinformatics, Vol. 6(Suppl 1), p.S9. 33. Rebholz-Schuhmann, D., Kirsch, H. and.

To evaluate the gene name tagging, we created a small doubly annotated test corpus. We selected a sample of 86 abstracts and had two annotators mark these ...