A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification
Paper summary The authors perform a hyperparameter search for a single-layer CNN on 9 different sentence classification datasets. They find that the optimal embedding initialisation, filter size and number of feature maps depends on the dataset and should be chosen through a search; ReLU and tanh are the best activation functions; 1-max pooling is the pooling method; dropout may help when the number of feature maps gets large. https://i.imgur.com/uUXVwb5.png
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A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification
Zhang, Ye and Wallace, Byron
arXiv e-Print archive - 2015 via Local Bibsonomy
Keywords: dblp


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