https://www.selleckchem.com/pr....oducts/molidustat-(b
Subsequently, the prediction model was tested by the validation-data set. The most accurate learning method was the support vector machine (SVM) algorithm (validation accuracy, 0.95; kappa statistic, 0.90; F-value, 0.94). The second-most accurate learning algorithm was Multi-layer perceptron. Unfortunately, Decision Tree, and Naive Bayes algorithms could not be fitted with our data set due to low accuracy ( less then 0.8). Conclusively, with an accuracy rate of 95.4% in the generalization performance evaluation, SVM was
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