Bayesian Optimization of Text Representations
Table 8: Comparisons on the 20 Newsgroups dataset for classifying documents into all topics. The disriminative RBM result is from drbm; compressive feature learning and LR-5-grams results are from compressive, and the distributed structured output result is from srikumar.
['[BOLD] Method', '[BOLD] Acc.']
The strong logistic regression baseline from \newcitecompressive uses all 5-grams, heuristic normalization, and elastic net regularization; our method found that unigrams and bigrams, with binary weighting and ℓ2 penalty, achieved far better results.