TY - GEN
T1 - Protein fold recognition with combined SVM-RDA classifier
AU - Chmielnicki, Wiesław
AU - Sta̧por, Katarzyna
PY - 2010
Y1 - 2010
N2 - Predicting the three-dimensional (3D) structure of a protein is a key problem in molecular biology. It is also an interesting issue for statistical methods recognition. There are many approaches to this problem considering discriminative and generative classifiers. In this paper a classifier combining the well-known Support Vector Machine (SVM) classifier with Regularized Discriminant Analysis (RDA) classifier is presented. It is used on a real world data set. The obtained results improve previously published methods.
AB - Predicting the three-dimensional (3D) structure of a protein is a key problem in molecular biology. It is also an interesting issue for statistical methods recognition. There are many approaches to this problem considering discriminative and generative classifiers. In this paper a classifier combining the well-known Support Vector Machine (SVM) classifier with Regularized Discriminant Analysis (RDA) classifier is presented. It is used on a real world data set. The obtained results improve previously published methods.
KW - RDA classifier
KW - Statistical classifiers
KW - Support Vectore Machine
KW - protein fold recognition
UR - https://www.scopus.com/pages/publications/77954566272
U2 - 10.1007/978-3-642-13769-3_20
DO - 10.1007/978-3-642-13769-3_20
M3 - Conference contribution
AN - SCOPUS:77954566272
SN - 3642137687
SN - 9783642137686
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 162
EP - 169
BT - Hybrid Artificial Intelligence Systems - 5th International Conference, HAIS 2010, Proceedings
T2 - 5th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2010
Y2 - 23 June 2010 through 25 June 2010
ER -