Apr 4, 2020 · We propose a new algorithm that predicts labels using a linear ensemble of labels from instance- and feature-based nearest neighbours.
Combining Instance and Feature Neighbors for Efficient Multi-label ...
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Finally our algorithm uses an inverted index during neighborhood search and scales to extreme datasets that have millions of instances, features and labels.
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Abstract Extreme multi-label classification problems occur in different applications such as prediction of tags or advertisements.
Feb 3, 2020 · We propose a new algorithm that predicts labels using a linear ensemble of instance- and feature-based nearest neighbours. We tackle the problem ...
Combining instance and feature neighbours for extreme multi-label classification. https://doi.org/10.1007/s41060-020-00209-1.
Mar 14, 2018 · We also compare the pruning ability and runtime performance of our k-nearest neighbours algorithm with state-of-the-art top-k query ...
Sep 1, 2020 · Combining instance and feature neighbours for extreme multi-label classification. Author: Feremans, Len. Cule, Boris ; Vens, Celine ; Goethals ...
Multilabel classification is an extension of conventional classification in which a single instance can be associated with multiple labels. Recent.
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Dec 1, 2023 · This work presents new neighbor-based approaches for solving MIML problems. On the one hand, MIML data are transformed into ML data and ML nearest neighbor ...
Extreme Multi-label Text Classification (XMC) involves learning a classifier that can assign an input with a subset of most relevant labels from millions of ...