Using genomic data and machine learning to predict antibiotic resistance: A tutorial paper
Fig 7
Final data visualization result from the last tutorial notebook.
The figure shows various bar graph subplots, with each one showing results for an individual evaluation metric. Only the highest-performing combinations of features for each metric are shown. The color key refers to the machine learning models (pink for logistic regression, green for random forest, yellow for extreme gradient-boosted trees, and blue for neural network). The black and white grid on the very bottom indicates which features were used to result in the highest performing model that predicted each antibiotic: ceftazidime (CTZ), cefotaxime (CTX), ampicillin (AMP), amoxicillin (AMX), amoxicillin-clavulanate (AMC), piperacillin-tazobactam (TZP), cefuroxime (CXM), cephalothin (CET), gentamicin (GEN), tobramycin (TBM), trimethoprim (TMP), ciprofloxacin (CIP).