Umber of features being reduced and the Y-axis represents the average training error in percentage over 100 training times counted in percentage. The training error increases significantly when 23 less relevant features are removed, as indicated by the red arrow. It is then suggested that at most 22 features could be eliminated.<p><b>Copyright information:</b></p><p>Taken from "A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data"</p><p>http://www.biomedcentral.com/1471-2105/9/325</p><p>BMC Bioinformatics 2008;9():325-325.</p><p>Published online 30 Jul 2008</p><p>PMCID:PMC2529326.</p><p></p
