Unraveling reported dreams with text analytics
Table 1: Micro-averaged performance of three classifiers on distinguishing dream reports from reports of real-world events on the 4.3M words corpus (39,480 documents in total). TPR = True Positive Rate. FPR = False Positive Rate. AUC = Area Under the Curve, # correct = number of correctly labeled documents.
['Approach', 'Prec', 'Recall', 'F1', 'TPR', 'FPR', 'AUC', '# correct']
All three approaches yield a precision and recall of 0.97, which indicates that the dream and non-dream reports can easily be distinguished with a small remaining margin of error. The Balanced Winnow classifier has a slightly higher number of correct classifications than Naive Bayes and SVM.