On the Decoding Process in Ternary Error-Correcting Output Codes

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Multi-class texture analysis in colorectal cancer histology (2016, methodology): “We employed support vector machines (SVM) with one-versus-one class decisions in an error-correcting output code multiclass model (ECOC) 30,31 .”
Beyond One-hot Encoding: lower dimensional target embedding (2018, methodology): “The most common decoding methods are the Hamming and Euclidean distances but there are more sophisticated approaches such as probabilistic-based decoding, especially with ternary codes [14].”