Sparse support vector machines with L_p penalty for biomarker identification

Mathematics

• Biomarkers 100%
• Support Vector Machine 97%
• Feature Selection 52%
• High-dimensional Data 44%
• Efficient Algorithms 33%
• Protein Sequence 27%
• High Throughput 27%
• Overfitting 26%
• Receiver Operating Characteristic Curve 23%
• Discrete Data 23%
• Learning Algorithm 22%
• Software Package 22%
• Cross-validation 21%
• Classifier 21%
• Regularization Parameter 21%
• Sparsity 20%
• MATLAB 20%
• Experimental Results 19%
• Learning 17%

Engineering & Materials Science

• Biomarkers 97%
• Support vector machines 62%
• Feature extraction 39%
• Software packages 25%
• Proteins 23%
• Learning algorithms 21%
• Classifiers 18%
• Throughput 18%

Medicine & Life Sciences

• Support Vector Machine 95%
• Biomarkers 50%
• Learning 28%
• Efficiency 21%
• ROC Curve 16%
• Single Nucleotide Polymorphism 16%
• Area Under Curve 15%
• Datasets 15%
• Software 14%
• Technology 12%
• Proteins 7%