Subsequently, 10,000 times of Y -random validation was performed
to assess the chance correlation. Plot ofR Y2 versusQ Y2 is shown in Figure 3d. The
average values of R Y2 andQ Y2 for the 10,000Y -random validation are 0.0521 and 0.0038, respectively, which
are much lower than the R 2 andQ 2LOO-CV of the developed
model. Therefore, the influence of randomness of the dataset itself on
the instability of the QSPR model can be ruled out. William plot was
used to visualize the developed model’s
application domain. Almost all the
plots, as depicted in Figure 4e , are within the tolerance of
three standard deviations of [-3, 3] and critical leverage level
(h *=0.1619). It therefore can be concluded that
the QSPR model is reliable to predict T g. The
values of relevant statistical parameters of QSPR model are shown inTable 1 .