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Extreme multi-label text classification is a prevalent task in industry, but it frequently encounters challenges in terms of machine learning perspectives, ...
Dec 10, 2023 · Extreme multi-label text classification is a prevalent task in industry, but it frequently en- counters challenges in terms of machine learn ...
This work defines an intrinsic evaluation based on greater-than constraints to provide a better understanding of this relatedness.
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What is extreme multi-label classification?
What are the methods of multilabel text classification?
Dec 2, 2023 · A new multi-label text classification method has been proposed. This method is based on joint attention and shared semantic space.
In this paper, we proposed a novel two-stage XMTC framework with candidate Retrieving and deep Ranking (XRR) to address those drawbacks.
The better approach to tackle such huge data imbalance is to weigh down frequent labels and boost rare labels data points while training the model. Focal Loss [ ...
Sep 12, 2024 · The task of learning from multi-label data can be addressed by methods that transform the multi-label classification problem into several single ...
Extreme Multi-Label Classification is a supervised learning problem where an instance may be associated with multiple labels.
Missing: Enhancing Addressing
This paper proposes a model of Label Attention and Correlation Networks (LACN) to address the challenges of classifying multi-label text and enhance ...
This paper presents the first attempt at applying deep learning to XMTC, with a family of new Convolutional Neural Network models which are tailored for multi- ...