However, such an approach ignores the effect of each change on
the overall usability of the WIS in hand. Namely, is it really worth
improving UWIS checklist item A1? It may or may not have much
effect on the overall usability although it is the lowest-rated item
by the end-users. The decision support system that is presented
in Section 2 proposes to calculate the criticality index for each of
the items in Table 2. To achieve this, I first determine the model
which best explains the relationships between the independent
variables (UWIS checklist items) and the dependent variable
(overall usability). Based on a 10-fold cross-validation evaluation,
various machine learning techniques (support vector machines
– SVM, neural networks – NN, and decision trees – DT) and a fundamental
statistical technique (multiple linear regression – MLR)
were employed and compared in terms of performance criteria