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Hands-On Natural Language Processing with Python by Rajalingappaa Shanmugamani, Rajesh Arumugam

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Deep learning for multi-label classification

In the paper on Large-scale Multi-label Text Classification – Revisiting Neural Networks (https://arxiv.org/abs/1312.5419), Nam et al. approaches this problem by using a deep multi-layer perceptron (MLP) with a hidden layer and output units producing scores for the labels. They use a label predictor which converts the label scores from the deep network to binary classes using thresholding based on a rank loss function. The details of this approach can be found in the aforementioned paper. 

The following diagram illustrates this approach:

Approach for multi-label classification

In the preceding diagram, ...

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