Is it normal to get a lot more variance in k folds cross-validation of an algorithm than in k repetitions of the same algorithm (neural network) on the same dataset?
k = k_folds = 10, same random seeds
Cross Validation Accuracy with k folds : 89.78% (+/-13.29%)
Mean Test Accuracy on k independent runs: 84.08% (+/-2.76%)
Thanks in advance