Search Results for author: Enrique Amigó

Found 2 papers, 1 papers with code

An Effectiveness Metric for Ordinal Classification: Formal Properties and Experimental Results

1 code implementation ACL 2020 Enrique Amigó, Julio Gonzalo, Stefano Mizzaro, Jorge Carrillo-de-Albornoz

In Ordinal Classification tasks, items have to be assigned to classes that have a relative ordering, such as positive, neutral, negative in sentiment analysis.

Classification General Classification +2

Combining Evaluation Metrics via the Unanimous Improvement Ratio and its Application to Clustering Tasks

no code implementations18 Jan 2014 Enrique Amigó, Julio Gonzalo, Javier Artiles, Felisa Verdejo

This paper introduces the Unanimous Improvement Ratio (UIR), a measure that complements standard metric combination criteria (such as van Rijsbergen's F-measure) and indicates how robust the measured differences are to changes in the relative weights of the individual metrics.

Clustering Text Clustering

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