Using this distance matrix it is now possible to apply K-Medoids clustering to determine the technology groupings predicted when each specific patent indicator subset is used. By comparing the predicted technology groupings to those expected from the earlier literature classifications (see section \ref{585124}), a confusion matrix is created for each patent indicator subset that shows the alignment between predicted and target groupings as shown in Fig. \ref{450923}. Fisher's exact test is then applied to each confusion matrix to calculate the probability of obtaining the observed clusters. In doing so, significant patent indicator subsets are identified based on those that have less than a 5% chance of natural occurrence.