Feature selection using a one dimensional naïve Bayes' classifier increases the accuracy of support vector machine classification of CDR3 repertoires

Keyphrases

• Complementarity-determining Region 3 (CDR3) 100%
• Support Vector Machine 100%
• Feature Selection 100%
• Support Vector Machine Classification 100%
• Freund Incomplete Adjuvant 100%
• Nave Bayes Classifier 100%
• Amino Acids 66%
• Immunization 66%
• Ovalbumin 66%
• Bayesian Classifier 66%
• Global Change 33%
• Test Validity 33%
• Vertebrates 33%
• High-throughput Sequencing 33%
• Sequence Data 33%
• T Cell Receptor 33%
• Adaptive Immunity 33%
• Leave-one-out 33%
• Html 33%
• Antigen Specificity 33%
• Feature Vector 33%
• Classification Strategy 33%
• DNA Recombination 33%
• Classification Score 33%
• Higher Classification 33%
• GitHub 33%
• Antigen Receptor 33%
• Complex Mixtures 33%
• CD4+ T Cell Response 33%
• Linear Motifs 33%
• Background Response 33%
• Ncbi 33%
• Two-stage Classification 33%

Biochemistry, Genetics and Molecular Biology

• Complementarity Determining Region 100%
• Support Vector Machine 100%
• Amino Acids 50%
• Ovalbumin 50%
• Eicosanoid Receptor 25%
• High Throughput Sequencing 25%
• T Cell 25%
• T Cell Receptor 25%
• Adaptive Immunity 25%
• Antigen Specificity 25%
• DNA Recombination 25%
• CD4 25%

Immunology and Microbiology

• Complementarity Determining Region 100%
• Support Vector Machine 100%
• Freund's Adjuvant 75%
• T Cell Receptor 25%
• Adaptive Immune System 25%
• T-Helper Cell 25%
• Antigen Specificity 25%
• High Throughput Sequencing 25%
• DNA Recombination 25%