RSL19BD at DBDC4:Ensemble of Decision Tree-based and LSTM-based Models
Table 17: Official results of MSE (NB, PB, B) for Je2
['[EMPTY]', 'IRS', 'MMK', 'MRK', 'TRF', 'ZNK']
It can be observed that due to the naive strategy above, all runs achieved poor performance with regard to IRS. To improve the result, we believe that the development data of IRS should be excluded from Jt2 and combined with Jt1. When predicting the labels for IRS in Je2, we should utilise the model trained with Jt1 instead of the one trained with Jt2. This proposed strategy requires us to either fix all training data to 30 turns in the LSTM-based model or develop a new model which accepts a shorter fixed turn length such as 5.