CloudScan - A configuration-free invoice analysis system using recurrent neural networks
TABLE II: Expected performance on next received invoice. Best results in bold.
['Field', 'F1 Baseline', 'F1 LSTM', 'Precision Baseline', 'Precision LSTM', 'Recall Baseline', 'Recall LSTM']
The LSTM model is slightly better than the baseline system with an average F1 of 0.891 compared to 0.887. In general the performance of the models is very similar, and close to the theoretical maximum performance given by the ceiling analysis. This means the classifiers both perform close to optimally for this experiment. The gains that can be had from improving upon the LSTM model further are just 0.034 average F1.