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Figure 4 | BMC Bioinformatics

Figure 4

From: A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data

Figure 4

Reduction of training errors in the feature selection phase. Features are reduced according to their relevance to the fragmentation process (Figure 2). The X-axis represents the number 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.

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