Prediction of protein sub-nuclear location by clustering mRMR ensemble feature selection
2010 20th International Conference on Pattern Recognition, ICPR 2010, İstanbul, Türkiye, 23 - 26 Ağustos 2010, ss.2572-2575, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Doi Numarası: 10.1109/icpr.2010.630
- Basıldığı Şehir: İstanbul
- Basıldığı Ülke: Türkiye
- Sayfa Sayıları: ss.2572-2575
- Boğaziçi Üniversitesi Adresli: Evet
Özet
In many applications of pattern recognition in the bioinformatics and biomedical fields, input variables are organized into natural partitions that are called views in the literature. Mutual information can be used in selecting a minimal yet capable subset of views. Ignoring the presence of views, dismantling them, and treating their variables intermixed along with those of others at best results in a complex uninterpretable predictive system for researchers in these fields. Moreover, it would require measuring or computing majority of the views. We use the clustering indices of the views and rank the views according to the unique information they have with the target using minimum redundancy-maximum relevance (mRMR) approach. We also propose an ensemble approach to reduce the random variations in clusterings. © 2010 IEEE.