Fine-grained Sentiment Classification on SST-5 (test)

53.4Accuracy (Fine-grained)

CNN-RNF-LSTM

Updated 4d ago

Evaluation Results

Method
CNN-RNF-LSTM 2018.08	53.4	-
Lei et al., 2017 2018.08	53.2	-
CNN-RNF-GRU 2018.08	53	-
NSE 2016.07	52.8	-
DMN 2016.07	52.1	-
GRU-maxpool 2018.08	51.7	-
LSTM-maxpool 2018.08	51.6	-
CT-LSTM 2016.07	51	-
GRU 2018.08	50.5	-
LSTM 2018.08	50.3	-
DRNN 2016.07	49.8	-
Bi-LSTM 2016.07	49.1	-
Paragraph Vector 2016.07	48.7	-
CNN-linear-filter 2018.08	48	-
CNN-MC 2016.07	47.4	-
2-layer LSTM 2016.07	46	-
RNTN 2016.07	45.7	-
Naïve Bayes 2014.05	-	0.59
SVMs 2014.05	-	0.593
Bigram Naïve Bayes 2014.05	-	0.581
Word Vector Averaging 2014.05	-	0.673
Recursive Neural Network 2014.05	-	0.568
Matrix Vector RNN 2014.05	-	0.556
Recursive Neural Tensor Network 2014.05	-	0.543
Paragraph Vector 2014.05	-	0.513