**4. Experimental Methodology**

In this section, we present a series of experiments in order to evaluate the performance of the proposed WvEnSL algorithm for X-ray classification against the most efficient ensemble self-labeled algorithms i.e., CST-Voting, DTCo and EnSL which utilize simple voting methodologies. The implementation code was written in JAVA, making use of the WEKA 3.9 Machine Learning Toolkit [27].

The performance of the classification algorithms is evaluated using the following performance metrics: *F*-measure (*F*1) and Accuracy (*Acc*). It is worth mentioning that *F*1 consists of a harmonic mean of precision and recall while Accuracy is the ratio of correct predictions of a classifier.
