ResearchIndex Home Stephen P. Curram and John Mingers. The emphasis of the research in the machine learning and statistics community has been on improving the accuracy of classifiers. These studies indicate that no algorithm is uniformly most accurate over all the datasets studied. S.P. Curram and J. Mingers. Usually there is a tradeoff between accuracy and efficiency, since improved accuracy tends to require more cost.
Conciseness measures the size of a classifier.
In the case of a classification tree, the tree size is reflected in both the number of leaf nodes and the depth of a tree. Interpretability refers to the level of understanding and insight that is provided by the learned model. The emphasis of the research in the machine learning and statistics community has been on improving the accuracy of classifiers. These studies indicate that no algorithm is uniformly most accurate over all the datasets studied. S.P. Curram and J. Mingers.