We carry out experiments with three different classification methods: SVMs with averaged embeddings, the Convolutional Neural Network of Kim (2014), and a Long Short Term Memory recurrent neural network (Hochreiter and Schmidhuber, 1997).
all hyperparameters of the network are the same as used in the original paper (Kim, 2014): stochastic dropout (Srivastava et al., 2014) with p = 0.5 on the penultimate layer, 100 filters for each filter region with filter regions of width 2,3 and 4.