Sample A: Cover Page of Thesis, Project, or Dissertation Proposal

The candidate gene list values were used as input for cross dataset validation of the classification
performance for the three algorithms described in Chapter 3: LDA, kNN, and RF. As described
there, the validation was carried out over 100 random permutations of both the training and test
datasets [10, 21]. The classification performance of the BaFL interpreted genes is benchmarked
against the RMA and dCHIP values input for the same classifiers. Model performance was
assessed by the AUC for the classification success [10, 14, 15]; results are presented in Figure
4.8.
Figure 4.8: Candidate list validation. Classification performance for the candidate list of 31 ProbeSets.
These ProbeSets were elucidated using the Bonferroni correction of the t-test results and are the set of
genes lying in the intersection between the two datasets along with the osteopontin Probeset. The BaFL
based values for these ProbeSets demonstrates the best performance for all three classification algorithms
and both reciprocal training and test scenarios.
107