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Sentiment Classification on Yelp Full (test)

35.28Test ErrorVDCNN
34.792838.081441.3744.6586Sep 4, 2015Oct 20, 2015Dec 5, 2015Jan 20, 2016Mar 6, 2016Apr 21, 2016Jun 6, 2016

Evaluation results

MethodLinks
VDCNNDepth=29, Pooling=Convolution2016.0635.28—
VDCNNDepth=29, Pooling=MaxPooling2016.0635.74—
VDCNNDepth=17, Pooling=MaxPooling2016.0636.07—
VDCNNDepth=17, Pooling=Convolution2016.0636.1—
VDCNNDepth=9, Pooling=MaxPooling2016.0636.73—
VDCNNDepth=29, Pooling=KMaxPooling2016.0637—
VDCNNDepth=17, Pooling=KMaxPooling2016.0637.41—
VDCNNDepth=9, Pooling=Convolution2016.0637.63—
Full Conv. (small, Th)Model Size=small, Case Sensitive=true, Thesaurus Augmentation=true2015.0937.95—
ConvAuthor=Zhang, data augmentation=true2016.0637.95—
VDCNNDepth=9, Pooling=KMaxPooling2016.0638.04—
Full Conv. (large)Model Size=large, Case Sensitive=true2015.0938.4—
BoW TFIDFTF-IDF Weighting=true2015.0940.14—
LSTM2015.0941.83—
BoW2015.0942.01—
ngrams2015.0943.74—
ngrams TFIDFTF-IDF Weighting=true2015.0945.2—
Bag-of-means2015.0947.46—
Bag-of-means2018.05—53.54
Deep CNNlayers=292018.05—64.26
fastText2018.05—60.4
fastText (bigram)features=bigram2018.05—63.9
Large word CNN2018.05—59.48
LSTM2018.05—58.17
Small word CNN2018.05—58.59
SWEM-aver2018.05—60.66
SWEM-concat2018.05—61.11
SWEM-hier2018.05—63.79
SWEM-max2018.05—59.63