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CoAL is a new algorithm which merges Co-Training, a well known multi-view semi-supervised machine learning algorithm, with Co-Testing, a multi-view active learning algorithm. CoAL, as well as Co-Training, were implemented in Java using the Weka API. In addition to these algorithms, the implementation offers an abstract class that eases the task of implementing new Co-Training style algorithms.

KNN-WEKA extends the current Weka k-nearest neighbor implementation by adding an example weighting function related to the distance from the current example to the query example. Moreover, KNN-Weka provides a distance function, known as the Heterogeneous Euclidean-VDM Metric (HVDM), which aims to better incorporate the information provided by nominal attributes.