A comparative study on feature selection in regression for predicting the affinity of TAP binding peptides

Keyphrases

• Binding Peptide 100%
• Feature Selection 100%
• Regression Model 66%
• Feature Selection Methods 66%
• K-nearest Neighbor (K-NN) 66%
• Least Squares Support Vector Regression (LSSVR) 66%
• Neighborhood Regression 66%
• Amino Acids 33%
• Frequency of Occurrence 33%
• Amino Acid Properties 33%
• TAP Transporter 33%
• Rough Set Model 33%
• Forward Feature Selection 33%
• Binary Sequences 33%

Biochemistry, Genetics and Molecular Biology

• Amino Acids 100%
• Support Vector Machine 100%
• Rough Set 50%