Skip to main content
. Author manuscript; available in PMC: 2019 Oct 1.
Published in final edited form as: Mol Pharm. 2018 Apr 26;15(10):4346–4360. doi: 10.1021/acs.molpharmaceut.8b00083

Figure 7.

Figure 7

Results of various classic machine learning algorithms and deep learning on the 153 compound TB test set using different evaluation metrics. The green bar represents the highest ROC AUC for each category. Machine learning algorithms compared include: Logistic Regression = LR, Adaboost Decision Trees = ADA, Random Forest = RF, Bernoulli Naïve-Bayesian = BNB and Support Vector Machines = SVM, DNN = Deep Neural Network with variable layers. Further details can be found in Supplemental Tables 2–6.