Text Compression for Sentiment Analysis via Evolutionary Algorithms
TABLE II: Average change in test accuracy (%) across all the data sets when PARSEC models were created for 75% compression rate.
['[BOLD] Algorithm', '[BOLD] Change in Test Accuracy', '[BOLD] Original Accuracy', '[BOLD] Compressed Accuracy']
We additionally wanted to determine the change in test accuracy when a much larger compression rate was used. Only certain algorithms were tested due to our limited access to the sentiment analysis algorithms. These results reveal that a large compression rate is achievable without a great loss in test accuracy: LingPipe obtained a loss of -3.3% accuracy.