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Hierarchy exploitation to detect missing annotations on hierarchical multi-label classification
The availability of genomic data has grown exponentially in the last decade, mainly due to the development of new sequencing technologies.
Explaining random forest prediction through diverse rulesets
Tree-ensemble algorithms, such as random forest, are effective machine learning methods popular for their flexibility, high performance, and robustness to overfitting.
An Adaptive Hybrid Active Learning Strategy with Free Ratings in Collaborative Filtering
This rating elicitation procedure enriches the interaction matrix with informative ratings and therefore assists the recommender system to better model the preferences of the users.
Deep tree-ensembles for multi-output prediction
In this paper, we specifically focus on two structured output prediction tasks, namely multi-label classification and multi-target regression.
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