Estimation of the breadth of CD4bs targeting HIV antibodies by molecular modeling and machine learning
Table 5
Comparison of the MLP classifier results with other machine learning techniques: MLP classifier with two hidden layers, Random Forests (RF with 31 trees), Supported Vector Machine (SVM with radial basis function kernel), and k-nearest neighbors (with 15 neighbors and weights assigned inversely proportional to the distance).
The reported data are the accuracy of the classifier (from the confusion matrix), and the Pearson, Spearman, slope and intercept for the correlation of the calculated and experimental breadths.