https://www.selleckchem.com/pr....oducts/amlexanox.htm
We analyzed the classification accuracy and the area under the curve (AUC). The highest accuracy was 0.82 for SVM, followed by 0.77 for RF, 0.74 for LR, 0.66 for DT, and 0.66 for boosted trees. The highest AUC was 0.53 for LR, followed by 0.52 for boosted trees, 0.48 for DT, and 0.47 for RF. Therefore, the best predictive model for this analysis was LR. The performance of the machine learning classifiers was not optimal owing to the small size of the dataset. The use of a machine learning model made it possible to predict recurrence i
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