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  • The Inria's Research Teams produce an annual Activity Report presenting their activities and their results of the year. These reports include the team members, the scientific program, the software developed by the team and the new results of the year. The report also describes the grants, contracts and the activities of dissemination and teaching. Finally, the report gives the list of publications of the year.

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Section: New Results

An Algorithm to Optimize the F-measure by Proper Weighting of Classification Errors

Participants: K. Bascol, R. Emonet, E. Fromont, A. Habrard, G. Metzler, M. Sebban

[16] proposes an F-Measure optimization algorithm with theoretical guarantees that can be used with any error-weighting learning method. The algorithm, iteratively generates a set of costs from the training set so that the final classifier has an F-measure close to optimal. The optimality of the F-measure is expressed using a finer upper bound as presented in [31]. Furthermore, we show that the costs obtained at each iteration of our method can drastically reduce the search space and thus converge quickly to the optimal parameters. The efficiency of the method is shown both in terms of F-measurement but also in terms of speed of convergence on several unbalanced datasets.