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ADABORD: a novel Adaptive Boosting approach for Ordinal classification

In this repository we provide the source code of the ADABORD method proposed in [incoming]. Moreover, we provide the code to reproduce the experiments in the paper, as well as the code to load the datasets used in the experiments.

📕 ADABORD is implemented in adabord.py and adabord_base.py files.

📘 The experiments are implemented in the experiments.py file. The remaining files implement the baseline methods used in the experiments.

📘 The experiments are executed on the TOC-UCO repository, the largest ordinal classification benchmarking archive to date.

💻 More about ordinal classification can be found in the dlordinal package, where several ordinal techniques are implemented, together with the most popular ordinal performance metrics.

📚 If you enjoyed this repository, we would appretiate a citation for the following work:

incoming

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Adaptive Boosting method of Ordinal targets

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