This is for multiclass classification. Before tuning the n_neighbors for KNN, these were the results:
Train Accuracy: 99.54%
Test Accuracy: 99.58%
ROC AUC Score: 99.86%
After finding the optimum n_neighbors, these were the results:
Train Accuracy: 99.64%
Test Accuracy: 99.67%
ROC AUC Score: 99.82%
My recall score went from 0.996 to 0.997. As we can see, the results improved without overfitting. But why did my ROC AUC score went down by 0.04? I thought the ROC AUC score increases when the model improves? My confusion matrices also improved: