Towards Using Social Media to Identify Individuals at Risk for Preventable Chronic Illness
Table 2: Random forest (RF) classifier performance on state-level data relative to majority baseline and Fried et al. (2014)’s best classifier. We include two versions of our classifier: the first keeps numeric features (e.g., word counts) as is, whereas the second discretizes numeric features to three bins.
['[ITALIC] Model', '[ITALIC] Accuracy']
Our second classifier, which used discretized numeric features and was the source of the quiz, performed 2% worse, but it still had acceptable accuracy, nearing 80%.