most citedMachine Learning for Multi-Output Regression: When should a holistic multivariate approach be preferred over separate univariate ones?

9 citations · 9 across the 2 of their papers we have counts for

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2 papers

stat.ML2022★ 9 cited

Machine Learning for Multi-Output Regression: When should a holistic multivariate approach be preferred over separate univariate ones?

Lena Schmid, Alexander Gerharz, Andreas Groll +1

Tree-based ensembles such as the Random Forest are modern classics among statistical learning methods. In particular, they are used for predicting univariate responses. In case of…

stat.ML2020

Deducing neighborhoods of classes from a fitted model

Alexander Gerharz, Andreas Groll, Gunther Schauberger

In todays world the request for very complex models for huge data sets is rising steadily. The problem with these models is that by raising the complexity of the models, it gets mu…