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Article
Active learning for hierarchical multi-label classification
Due to technological advances, a massive amount of data is produced daily, presenting challenges for application areas where data needs to be labelled by a domain specialist or by expensive procedures, in orde...
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Chapter and Conference Paper
Explaining a Random Survival Forest by Extracting Prototype Rules
Tree-ensemble algorithms and specifically Random Survival Forests (RSF) have emerged as prominently powerful methods for survival data analysis. Tree-ensembles are very accurate, robust, resilient to overfitti...
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Chapter and Conference Paper
An Adaptive Hybrid Active Learning Strategy with Free Ratings in Collaborative Filtering
Recommender systems are information retrieval methods that predict user preferences to personalize services. These systems use the feedback and the ratings provided by users to model the behavior of users and ...