Carlos Santos's Library tagged icml →  View Popular

this workshop intends to continue the debate within the
machine learning community into how we evaluate new algorithms.

In the course of three previous workshops, the debate has evolved to focus around
the following issues which have captured the interest of the community:

* the role of experiments in evaluation

* the use of one, community wide, evaluation measure (e.g., Accuracy, AUC,
F-measure)

* the relevance of statistical tests to evaluation

* the effectiveness of the UCI data sets for evaluation

* the need for sharing and characterizing benchmark data sets in general

* how to promote the views of this workshop to the rest of the community