Figure 8.

Prediction results from the hierarchical inverse and classical metamodelling. A) R2-values from the hierarchical NPLSR test set prediction of the parameters from the state variable time series using six regional regression models, using 18, 19, 19, 18, 19 and 17 NPLSR factors, respectively. The clustering was done on the global <a onClick="popup('http://www.biomedcentral.com/1752-0509/6/88/mathml/M13','MathML',630,470);return false;" target="_blank" href="http://www.biomedcentral.com/1752-0509/6/88/mathml/M13">View MathML</a> factors, using 19 factors. B) R2-values from the hierarchical NPLSR test set prediction of the state variable trajectories from the parameters using six regional regression models, all using 9 NPLSR factors. The same clusters as in the inverse metamodelling were used.

T√łndel et al. BMC Systems Biology 2012 6:88   doi:10.1186/1752-0509-6-88
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