Where, λ i is the matrix eigenvalue, and the
is
the Hermite matrix.
2.4 Model Validation
These QSPR models were quantitatively assessed by several statistical
criteria as relative deviation (RD ), the Fisher significance
parameter (F ) and the average absolute relative deviation
percentage (AARD %). The predictability of the model is
supported by R2training for the
training set and R2testing for
the testing set. In addition, Leave-one-out (LOO) validation was
utilized to evaluate the robustness of this QSPR model
(Q 2). Y -randomization test was utilized
to avoid the possibility of chance correlation in the modelling
work.32,49